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Actuators
Volume 13
Issue 9
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Actuators, Volume 13, Issue 9 (September 2024) – 57 articles

Cover Story (view full-size image): This work presents both the design and characterisation of a novel hybrid pneumatic rotational actuator. The air chamber and auxetic structure of the actuator can exploit the hyper-elastic properties of a soft fabrication material to optimise the response and to extend the operational range of the actuator. The integration of the soft structure within a rigid frame is inspired by the musculoskeletal structure of a lobster leg. Hyper-elastic and 3D-printable materials are used to fabricate the actuator through an FDM process. The experimental results show the linearity, good repeatability, and sensitivity of the actuator response vs. pneumatic pressure input, apart from a small percentage of hysteresis, which is ten times less than that which is observed in commercial soft pneumatic actuators. View this paper
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22 pages, 4908 KiB  
Article
Fault Diagnosis of Low-Noise Amplifier Circuit Based on Fusion Domain Adaptation Method
by Chao Zhang, Peng Du, Dingyu Zhou, Zhijie Dong, Shilie He and Zhenwei Zhou
Actuators 2024, 13(9), 379; https://doi.org/10.3390/act13090379 - 23 Sep 2024
Viewed by 651
Abstract
The Low-Noise Amplifier (LNA) is a critical component of Radio Frequency (RF) receivers. Therefore, the accuracy of LNA fault diagnosis significantly impacts the overall performance of the entire RF receiver. Traditional LNA fault diagnosis is typically conducted under fixed conditions, but varying factors [...] Read more.
The Low-Noise Amplifier (LNA) is a critical component of Radio Frequency (RF) receivers. Therefore, the accuracy of LNA fault diagnosis significantly impacts the overall performance of the entire RF receiver. Traditional LNA fault diagnosis is typically conducted under fixed conditions, but varying factors in practical applications often alter the circuit’s parameters and reduce diagnostic accuracy. To address the issue of decreased fault diagnosis accuracy under varying external or internal conditions, a fusion domain adaptation method based on Convolutional Neural Networks (CNNs), referred to as FDA, is proposed. Firstly, a domain-adaptive diagnostic model was established based on the feature extraction capabilities of CNNs. The powerful deep feature extraction capabilities of CNNs and the adaptability of domain adaptation methods to changing conditions are leveraged to enhance both the generalization ability of diagnostic models and the environmental adaptability of diagnostic techniques. Secondly, the fusion of feature-mapping domain adaptation and adversarial domain adaptation further enhances the convergence speed and diagnostic accuracy of the LNA cross-domain fault diagnosis model in the target domain. Finally, various cross-domain experiments were conducted. The FDA method achieved an average fault diagnosis rate of 90.19%, which represents an improvement of over 30% in accuracy compared to a CNN and also shows enhancements over individual domain-adaptation methods. Full article
(This article belongs to the Section Control Systems)
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31 pages, 15195 KiB  
Article
Redundancy Control Strategy for a Dual-Redundancy Steer-by-Wire System
by Ke Wang, Baojun Qu and Mingwang Gao
Actuators 2024, 13(9), 378; https://doi.org/10.3390/act13090378 - 23 Sep 2024
Viewed by 533
Abstract
Currently, key factors hindering application of steer-by-wire systems are their inadequate safety and reliability, which are significant criteria for evaluating automotive active safety. Based on the steer-by-wire platform, a dual-redundant steering motor control system is proposed, featuring dual three-phase permanent magnet synchronous motors [...] Read more.
Currently, key factors hindering application of steer-by-wire systems are their inadequate safety and reliability, which are significant criteria for evaluating automotive active safety. Based on the steer-by-wire platform, a dual-redundant steering motor control system is proposed, featuring dual three-phase permanent magnet synchronous motors as execution motors, achieving redundancy from hardware. A torque vector-space-decoupling control method is introduced for these motors to ensure balanced and stable torque output. Upon a fault, fault-tolerant measures are taken by disconnecting power supply to the affected motor, which, despite reducing system functionality, allows for normal steering control. This research starts with modeling the dual three-phase motors to construct a simulation model. It then proceeds with hardware-in-the-loop testing integrated with the dual-redundancy steer-by-wire control system, conducting tests under dual-lane-change trajectory conditions. Finally, a steering system fault is simulated to assess fault handling and functional degradation. These experiments confirmed that the proposed method enabled balanced torque output from the dual three-phase motors in the redundant steering control and facilitated fault-tolerant processing post fault, ensuring the vehicle’s steering functions were maintained. Full article
(This article belongs to the Special Issue Actuator Fault Diagnosis, State Detection and Fault Tolerant Control for Ground and Rail Vehicles)
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22 pages, 17224 KiB  
Article
Study and Experimental Verification on Anti-Disturbance Control Strategy for Electro-Mechanical Servo Systems
by Shicheng Zheng, Deyi Wang, Jingkun Wei, Yunjie Yang and Jihong Zhu
Actuators 2024, 13(9), 377; https://doi.org/10.3390/act13090377 - 23 Sep 2024
Viewed by 531
Abstract
With technological advances and industrial upgrading, electro-mechanical actuators (EMAs) have gradually replaced traditional hydraulic actuation systems. During operation, force servo systems inevitably suffer from external force or position disturbances, thus affecting the output performance of the system. Therefore, it is of significant engineering [...] Read more.
With technological advances and industrial upgrading, electro-mechanical actuators (EMAs) have gradually replaced traditional hydraulic actuation systems. During operation, force servo systems inevitably suffer from external force or position disturbances, thus affecting the output performance of the system. Therefore, it is of significant engineering application value to develop EMA anti-disturbance control strategies that exhibit strong robustness and are more easily applicable to engineering practice. In this study, an open-loop transfer function of the system with command signals and disturbance signals as inputs was established based on the nonlinear mathematical models built for the core components of EMAs. To overcome the impact of external position disturbances on the motion performance of the force servo system, a proportional integral derivative (PID) controller was introduced and a high-order transfer function associated with various parameters such as speed and acceleration was derived and obtained as feedforward compensation based on the mathematical model. By incorporating a three-loop PID controller, the impact of external disturbance forces on the motion performance of the position servo system was overcome and the tracking accuracy of the system was also improved. Finally, simulation models were built using AMESim software (AMESim 2020, LMS Imagine.Lab, Roanne, France) and a dual-channel EMA performance testing system was developed. Simulation and test results indicated that both anti-disturbance control methods exhibited strong robustness and excellent anti-disturbance performance, with the control accuracy and dynamic performance almost unaffected by disturbances. This verified the correctness of the single-channel EMA anti-disturbance control strategy and the usability of the simulation model. Full article
(This article belongs to the Section Control Systems)
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21 pages, 2588 KiB  
Article
A Deep Reinforcement Learning Approach to Injection Speed Control in Injection Molding Machines with Servomotor-Driven Constant Pump Hydraulic System
by Zhigang Ren, Peng Tang, Wen Zheng and Bo Zhang
Actuators 2024, 13(9), 376; https://doi.org/10.3390/act13090376 - 23 Sep 2024
Viewed by 746
Abstract
The control of the injection speed in hydraulic injection molding machines is critical to product quality and production efficiency. This paper analyzes servomotor-driven constant pump hydraulic systems in injection molding machines to achieve optimal tracking control of the injection speed. We propose an [...] Read more.
The control of the injection speed in hydraulic injection molding machines is critical to product quality and production efficiency. This paper analyzes servomotor-driven constant pump hydraulic systems in injection molding machines to achieve optimal tracking control of the injection speed. We propose an efficient reinforcement learning (RL)-based approach to achieve fast tracking control of the injection speed within predefined time constraints. First, we construct a precise Markov decision process model that defines the state space, action space, and reward function. Then, we establish a tracking strategy using the Deep Deterministic Policy Gradient RL method, which allows the controller to learn optimal policies by interacting with the environment. Careful attention is also paid to the network architecture and the definition of states/actions to ensure the effectiveness of the proposed method. Extensive numerical results validate the proposed approach and demonstrate accurate and efficient tracking of the injection velocity. The controller’s ability to learn and adapt in real time provides a significant advantage over the traditional Proportion Integration Differentiation controller. The proposed method provides a practical solution to the challenge of maintaining accurate control of the injection speed in the manufacturing process. Full article
(This article belongs to the Section Control Systems)
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19 pages, 7572 KiB  
Article
Adaptive Neural Network Control of Four-Switch Buck–Boost Converters
by Luoyao Ren, Dazhi Wang and Yupeng Zhang
Actuators 2024, 13(9), 375; https://doi.org/10.3390/act13090375 - 23 Sep 2024
Viewed by 607
Abstract
Based on the adaptive control structure of neural networks, this paper proposes a novel output voltage control strategy for DC converters. The strategy regulates the inductor current to maintain a constant voltage by adjusting the duty cycle of four-switch buck—boost (FSBB) converters. A [...] Read more.
Based on the adaptive control structure of neural networks, this paper proposes a novel output voltage control strategy for DC converters. The strategy regulates the inductor current to maintain a constant voltage by adjusting the duty cycle of four-switch buck—boost (FSBB) converters. A nonlinear average model for the FSBB converter, derived from its energy consumption, is introduced, and its effectiveness is demonstrated through simulations. The simulations confirm that the FSBB converter enables zero-voltage switching (ZVS) of the four switches across the entire operating voltage range. The comparative simulation results show that the proposed control strategy achieves faster voltage regulation while ensuring ZVS, leading to improved converter performance across the full power range. Full article
(This article belongs to the Section Control Systems)
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15 pages, 5427 KiB  
Article
Enhanced Hand–Eye Coordination Control for Six-Axis Robots Using YOLOv5 with Attention Module
by Yulan Wei, Chenghao Liao, Liang Zhang, Qingzhu Zhang, Yang Shen, Ying Zang, Siqi Li and Haibo Huang
Actuators 2024, 13(9), 374; https://doi.org/10.3390/act13090374 - 20 Sep 2024
Viewed by 686
Abstract
Utilizing machine vision technology based on YOLOv5, a six-axis robot can quickly identify and classify targets. However, when the YOLOv5 model is used for the recognition and grasping of small workpieces, issues such as low precision and missed detections frequently occur. This paper [...] Read more.
Utilizing machine vision technology based on YOLOv5, a six-axis robot can quickly identify and classify targets. However, when the YOLOv5 model is used for the recognition and grasping of small workpieces, issues such as low precision and missed detections frequently occur. This paper proposes an enhanced object recognition algorithm, integrating a CBAM attention module and an improved loss function into YOLOv5 to control the hand–eye coordination of the six-axis robot during grasping. The CBAM attention module is incorporated into the backbone network of YOLOv5 to enhance its feature extraction capabilities, while the original loss function is modified to accelerate convergence and improve regression accuracy. An experimental platform for six-axis robot hand–eye coordination grasping was built, and grasping experiments were conducted. The proposed method significantly improves the robot’s grasping accuracy, with a 99.59% mAP0.5 and a 90.83% successful grasping rate, effectively addressing the challenges of low accuracy and missed detections in traditional systems. Full article
(This article belongs to the Section Actuators for Robotics)
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22 pages, 8465 KiB  
Article
Fault Diagnosis Method of Permanent Magnet Synchronous Motor Based on WCNN and Few-Shot Learning
by Chao Zhang, Fei Wang, Xiangzhi Li, Zhijie Dong and Yubo Zhang
Actuators 2024, 13(9), 373; https://doi.org/10.3390/act13090373 - 20 Sep 2024
Viewed by 430
Abstract
With the continuous development of actuator technology, the Electro-Mechanical Actuator (EMA) is gradually becoming the first choice in the aviation field. Permanent Magnet Synchronous Motor (PMSM) is one of the core components of EMA, and its healthy state determines the working performance of [...] Read more.
With the continuous development of actuator technology, the Electro-Mechanical Actuator (EMA) is gradually becoming the first choice in the aviation field. Permanent Magnet Synchronous Motor (PMSM) is one of the core components of EMA, and its healthy state determines the working performance of EMA. In this paper, the interturn short-circuit fault of PMSM is taken as the typical fault, and a new fault diagnosis framework is proposed based on a wide-kernel convolutional neural network (WCNN) and few-shot learning. Firstly, the wide convolution kernel is added as the first layer to extract short-time features while automatically learning deeply oriented features oriented to diagnosis and removing useless features. Then, the twin neural network is introduced to establish a wide kernel convolutional neural network, which can also achieve good diagnostic results under a few-shot learning framework. The effectiveness of the proposed method is verified by the general data set. The results show that the accuracy of few-shot learning is 9% higher than that of WCNN when the fault data are small. Finally, a fault test platform was built for EMA to collect three-phase current data under different fault states, and the collected data were used to complete the fault diagnosis of PMSM. With limited data, the accuracy of few-shot learning increased by 8% on average compared with WCNN, which has good engineering value. Full article
(This article belongs to the Special Issue Fault Detection and Isolation, Fault Tolerant Control for Autonomous and Transport Vehicles)
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14 pages, 3221 KiB  
Article
Experimental Verification of a Two-Motor-Two-Pump Motor-Controlled Hydraulic Cylinder with Throttle-Free Passive Load-Holding Capability in Four-Quadrant Operations
by Wei Zhao, Morten Kjeld Ebbesen, Michael Rygaard Hansen and Torben Ole Andersen
Actuators 2024, 13(9), 372; https://doi.org/10.3390/act13090372 - 20 Sep 2024
Viewed by 463
Abstract
Among various motor-controlled hydraulic cylinder (MCC) topologies, the two-motor-two-pump (2M2P) MCC distinguishes itself through several notable advantages, including precise cylinder pressure control and eliminating mode switch oscillations. Nevertheless, there are challenges remaining in fully realizing its operations across four quadrants and establishing an [...] Read more.
Among various motor-controlled hydraulic cylinder (MCC) topologies, the two-motor-two-pump (2M2P) MCC distinguishes itself through several notable advantages, including precise cylinder pressure control and eliminating mode switch oscillations. Nevertheless, there are challenges remaining in fully realizing its operations across four quadrants and establishing an effective load-holding function within these operations. This study bridges this gap by implementing a 2M2P MCC prototype on a laboratory knuckle boom crane, enabling operation across all four quadrants. Experimental results indicate that position tracking errors remain within ±2.5 mm across three cases, which is well below 1% of the total cylinder travels in the experiments. Furthermore, smooth intersection of cylinder-bore-side and rod-side pressures is observed during transitions between quadrants. In conclusion, the proposed 2M2P MCC demonstrates seamless operation throughout all quadrants, with the load-holding function smoothly activating and deactivating in all four quadrants. Full article
(This article belongs to the Special Issue Control of Hydraulic Robotic Manipulators)
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17 pages, 2499 KiB  
Article
Incremental Sliding Mode Control for Predefined-Time Stability of a Fixed-Wing Electric Vertical Takeoff and Landing Vehicle Attitude Control System
by Jujiang Liu and Yusong Tan
Actuators 2024, 13(9), 371; https://doi.org/10.3390/act13090371 - 20 Sep 2024
Viewed by 535
Abstract
This paper presents a novel incremental sliding mode control scheme to address the attitude-tracking issue in both the helicopter and airplane modes of an electric vertical takeoff and landing vehicle, guaranteeing the stabilization of the attitude-tracking error within a predefined time. Firstly, an [...] Read more.
This paper presents a novel incremental sliding mode control scheme to address the attitude-tracking issue in both the helicopter and airplane modes of an electric vertical takeoff and landing vehicle, guaranteeing the stabilization of the attitude-tracking error within a predefined time. Firstly, an incremental model of the vehicle’s attitude control system with external disturbances is established. The high-order terms of the incremental model and instantaneous perturbations are retained as lumped terms rather than directly discarding them to ensure the accuracy of the incremental model. Then, a novel nonsingular sliding surface is developed. Once the ideal sliding motion is established, the states on the sliding surface will converge to the equilibrium point within a predefined time. Furthermore, a predefined-time incremental sliding mode controller is developed by using sliding mode control and incremental control techniques. It effectively reduces the reliance on the model information and attenuates the effects of external disturbances. The predefined-time stability of the entire controlled system is rigorously proven using Lyapunov theory. Finally, numerical simulation examples verify the effectiveness of the proposed control scheme. Full article
(This article belongs to the Special Issue Advances in Dynamics and Motion Control of Unmanned Aerial/Underwater/Ground Vehicles)
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22 pages, 4873 KiB  
Article
Path Planning for Wall-Climbing Robots Using an Improved Sparrow Search Algorithm
by Wenyuan Xu, Chao Hou, Guodong Li and Chuang Cui
Actuators 2024, 13(9), 370; https://doi.org/10.3390/act13090370 - 20 Sep 2024
Viewed by 606
Abstract
Traditional path planning algorithms typically focus only on path length, which fails to meet the low energy consumption requirements for wall-climbing robots in bridge inspection. This paper proposes an improved sparrow search algorithm based on logistic–tent chaotic mapping and differential evolution, aimed at [...] Read more.
Traditional path planning algorithms typically focus only on path length, which fails to meet the low energy consumption requirements for wall-climbing robots in bridge inspection. This paper proposes an improved sparrow search algorithm based on logistic–tent chaotic mapping and differential evolution, aimed at addressing the issue of the sparrow search algorithm’s tendency to fall into local optima, thereby optimizing path planning for bridge inspection. First, the initial population is optimized using logistic–tent chaotic mapping and refracted opposition-based learning, with dynamic adjustments to the population size during the iterative process. Second, improvements are made to the position updating formulas of both discoverers and followers. Finally, the differential evolution algorithm is introduced to enhance the global search capability of the algorithm, thereby reducing the robot’s energy consumption. Benchmark function tests verify that the proposed algorithm exhibits superior optimization capabilities. Further path planning simulation experiments demonstrate the algorithm’s effectiveness, with the planned paths not only consuming less energy but also exhibiting shorter path lengths, fewer turns, and smaller steering angles. Full article
(This article belongs to the Section Actuators for Robotics)
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17 pages, 3062 KiB  
Article
A Hinge Moment Alleviation Control Strategy for Morphing Tail Aircraft Based on a Data-Driven Method
by Rui Cao and Huitao Lyu
Actuators 2024, 13(9), 369; https://doi.org/10.3390/act13090369 - 19 Sep 2024
Viewed by 574
Abstract
Morphing airplane technology is currently a focal point of research. For morphing airplanes, besides effective morphing strategies and control schemes, the hinge moment at the root of the vertical tail during morphing is a critical factor influencing flight safety. To prevent failure in [...] Read more.
Morphing airplane technology is currently a focal point of research. For morphing airplanes, besides effective morphing strategies and control schemes, the hinge moment at the root of the vertical tail during morphing is a critical factor influencing flight safety. To prevent failure in tail morphing due to excessive hinge moments, this paper analyzes the hinge moment characteristics of the variable vertical tail structure in high-speed flight, based on a flying wing model from the China Aerodynamics Research and Development Center. The proposed adaptive morphing tail hinge moment reduction (AMTHR) method is model-free, utilizing real-time data to dynamically adjust the rudder and reduce hinge moments without requiring prior knowledge of system dynamics. This method utilizes the concept of extremum-seeking control by introducing periodic perturbations to the system and adjusting the control input based on their impact on the output. This approach drives the output toward an extremum point, enabling real-time reduction of the vertical tail hinge moment. Finally, the simulation analysis is carried out under the conditions of no wind and gust disturbance, and the effect of this method on the load reduction of the tail hinge moment is verified. Full article
(This article belongs to the Special Issue Aerospace Mechanisms and Actuation—Second Edition)
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17 pages, 6630 KiB  
Article
An Actively Vision-Assisted Low-Load Wearable Hand Function Mirror Rehabilitation System
by Zheyu Chen, Huanjun Wang, Yubing Yang, Lichao Chen, Zhilong Yan, Guoli Xiao, Yi Sun, Songsheng Zhu, Bin Liu, Liang Li and Jianqing Li
Actuators 2024, 13(9), 368; https://doi.org/10.3390/act13090368 - 19 Sep 2024
Viewed by 530
Abstract
The restoration of fine motor function in the hand is crucial for stroke survivors with hemiplegia to reintegrate into daily life and presents a significant challenge in post-stroke rehabilitation. Current mirror rehabilitation systems based on wearable devices require medical professionals or caregivers to [...] Read more.
The restoration of fine motor function in the hand is crucial for stroke survivors with hemiplegia to reintegrate into daily life and presents a significant challenge in post-stroke rehabilitation. Current mirror rehabilitation systems based on wearable devices require medical professionals or caregivers to assist patients in donning sensor gloves on the healthy side, thus hindering autonomous training, increasing labor costs, and imposing psychological burdens on patients. This study developed a low-load wearable hand function mirror rehabilitation robotic system based on visual gesture recognition. The system incorporates an active visual apparatus capable of adjusting its position and viewpoint autonomously, enabling the subtle monitoring of the healthy side’s gesture throughout the rehabilitation process. Consequently, patients only need to wear the device on their impaired hand to complete the mirror training, facilitating independent rehabilitation exercises. An algorithm based on hand key point gesture recognition was developed, which is capable of automatically identifying eight distinct gestures. Additionally, the system supports remote audio–video interaction during training sessions, addressing the lack of professional guidance in independent rehabilitation. A prototype of the system was constructed, a dataset for hand gesture recognition was collected, and the system’s performance as well as functionality were rigorously tested. The results indicate that the gesture recognition accuracy exceeds 90% under ten-fold cross-validation. The system enables operators to independently complete hand rehabilitation training, while the active visual system accommodates a patient’s rehabilitation needs across different postures. This study explores methods for autonomous hand function rehabilitation training, thereby offering valuable insights for future research on hand function recovery. Full article
(This article belongs to the Special Issue Actuators and Robotic Devices for Rehabilitation and Assistance)
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18 pages, 1163 KiB  
Article
Adaptive Nonsingular Fast Terminal Sliding Mode Control for Shape Memory Alloy Actuated System
by Xiaoguang Li, Wenzhuo Zhi, Enming Shi, Xiaoliang Fan, Ming Zhao and Bi Zhang
Actuators 2024, 13(9), 367; https://doi.org/10.3390/act13090367 - 19 Sep 2024
Viewed by 705
Abstract
Due to its high power-to-weight ratio, low weight, and silent operation, shape memory alloy (SMA) is widely used as a muscle-like soft actuator in intelligent bionic robot systems. However, hysteresis nonlinearity and multi-valued mapping behavior can severely impact trajectory tracking accuracy. This paper [...] Read more.
Due to its high power-to-weight ratio, low weight, and silent operation, shape memory alloy (SMA) is widely used as a muscle-like soft actuator in intelligent bionic robot systems. However, hysteresis nonlinearity and multi-valued mapping behavior can severely impact trajectory tracking accuracy. This paper proposes an adaptive nonsingular fast terminal sliding mode control (ANFTSMC) scheme aimed at enhancing position tracking performance in SMA-actuated systems by addressing hysteresis nonlinearity, uncertain dynamics, and external disturbances. Firstly, a simplified third-order actuator model is developed and a variable gain extended state observer (VGESO) is employed to estimate unmodeled dynamics and external disturbances within finite time. Secondly, a novel nonsingular fast terminal sliding mode control (NFTSMC) law is designed to overcome singularity issues, reduce chattering, and guarantee finite-time convergence of the system states. Finally, the ANFTSMC scheme, integrating NFTSMC with VGESO, is proposed to achieve precise position tracking for the prosthetic hand. The convergence of the closed-loop control system is validated using Lyapunov’s stability theory. Experimental results demonstrate that the external pulse disturbance error of ANFTSMC is 8.19°, compared to 19.21° for the comparative method. Furthermore, the maximum absolute error for ANFTSMC is 0.63°, whereas the comparative method shows a maximum absolute error of 1.03°. These results underscore the superior performance of the proposed ANFTSMC algorithm. Full article
(This article belongs to the Special Issue Shape Memory Alloy (SMA) Actuators and Their Applications)
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17 pages, 655 KiB  
Article
Adaptive Predefined Time Control for Strict-Feedback Systems with Actuator Quantization
by Wentong Zhang and Bo Yu
Actuators 2024, 13(9), 366; https://doi.org/10.3390/act13090366 - 19 Sep 2024
Viewed by 502
Abstract
An adaptive predefined-time quantized control issue is considered for strict-feedback systems with actuator quantization. To handle the unknown nonlinearities of a system, the neural networks are first applied to model them. To analyze the predefined-time stability under approximation error, a stability lemma is [...] Read more.
An adaptive predefined-time quantized control issue is considered for strict-feedback systems with actuator quantization. To handle the unknown nonlinearities of a system, the neural networks are first applied to model them. To analyze the predefined-time stability under approximation error, a stability lemma is first introduced. Then, a refreshing predefined-time quantized control strategy is presented. Compared with the existing control studies for actuator quantization, the stability time is not influenced by the initial state and can be set in advance. Furthermore, unlike the available predefined-time control studies, a new parameter adaptive law and virtual controllers are designed. This design not only ensures the predefined-time stability, but overcomes the singularities of system in coventional backstepping control design because of repeating differentiation for virtual controllers. Full article
(This article belongs to the Special Issue Neural Networks-Based Modeling and Control for Uncertain Dynamical Systems)
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14 pages, 4787 KiB  
Article
Study on the Vibration Reduction Effect of Piezoelectric Actuation on Flexible Tilting Pad Bearings with Different Structural Parameters
by Yanyan Qin, Xiaojing Wang, Guangyao Huang, Xiaohan Zhang and Shuxiang Yi
Actuators 2024, 13(9), 365; https://doi.org/10.3390/act13090365 - 19 Sep 2024
Viewed by 543
Abstract
To improve the vibration performance of oil-lubricated tilting pad bearing systems, this paper investigates the impact of different structural parameters on the vibration reduction effect of piezoelectric actuators on flexible tilting pad bearings. Four sets of flexible tilting pad bearings were designed and [...] Read more.
To improve the vibration performance of oil-lubricated tilting pad bearing systems, this paper investigates the impact of different structural parameters on the vibration reduction effect of piezoelectric actuators on flexible tilting pad bearings. Four sets of flexible tilting pad bearings were designed and manufactured, including a flexible hinge tilting pad bearing and three sets of double-layer spring-supported flexible tilting pad bearings with different parameters. The radial displacement of the bearing load pad was controlled to varying degrees using a piezoelectric actuator, and semi-active control experiments were conducted on the flexible tilting pad bearings. The experimental results show that appropriately reducing the radial clearance and the stiffness of the bearing’s flexible structure can effectively suppress vibrations, enhance the vibration reduction effect of the piezoelectric actuation, and increase the stability of the bearing-rotor system. This study is of significant importance for the design of flexible tilting pad bearings and the vibration suppression of rotor systems. Full article
(This article belongs to the Section Control Systems)
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17 pages, 6887 KiB  
Article
Research on the Safety Design and Trajectory Planning for a New Dual Upper Limb Rehabilitation Robot
by Chenchen Zhang, Hao Yan, Jian Wei, Fangcao Zhang, Zhongliang Shi and Xingao Li
Actuators 2024, 13(9), 364; https://doi.org/10.3390/act13090364 - 18 Sep 2024
Viewed by 487
Abstract
The increasing utilization of upper limb rehabilitation robots in rehabilitation therapy has brought to light significant safety concerns regarding their mechanical structures and control systems. This study focuses on a six degrees of freedom (DOF) upper limb rehabilitation robot, which has been designed [...] Read more.
The increasing utilization of upper limb rehabilitation robots in rehabilitation therapy has brought to light significant safety concerns regarding their mechanical structures and control systems. This study focuses on a six degrees of freedom (DOF) upper limb rehabilitation robot, which has been designed with an emphasis on safety through careful consideration of its mechanical structure and trajectory planning. Various parameter schemes for the shoulder joint angles were proposed, and the robotic arm’s structure was developed by analyzing the spatial motion trajectories of the shoulder joint motor. This design successfully achieves the objective of minimizing the installation space while maximizing the range of motion. Additionally, an enhanced artificial field method is introduced to facilitate the planning of self-collision avoidance trajectories for dual-arm movements. This approach effectively mitigates the risk of collisions between the robotic arm and the human body, as well as between the two robotic arms, during movement. The efficacy of this method has been validated through experimental testing. Full article
(This article belongs to the Section Actuators for Robotics)
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16 pages, 4405 KiB  
Article
Pneumatically Actuated Torsion Motor for the Transverse Rehabilitation of the Neck Joint
by Sarah Mareş, Andrea Deaconescu and Tudor Deaconescu
Actuators 2024, 13(9), 363; https://doi.org/10.3390/act13090363 - 18 Sep 2024
Viewed by 488
Abstract
Work-related musculoskeletal disorders affect a large number of people, diminishing inter alia, their workplace efficiency. For this reason, rehabilitation procedures and equipment are called for, designed to expedite the swift reintegration of patients into daily activity. Within this context, this paper proposes a [...] Read more.
Work-related musculoskeletal disorders affect a large number of people, diminishing inter alia, their workplace efficiency. For this reason, rehabilitation procedures and equipment are called for, designed to expedite the swift reintegration of patients into daily activity. Within this context, this paper proposes a novel constructive solution of a device that ensures rehabilitation through the transverse passive mobilization of the neck joint. This paper introduces a torsion motor actuated by two pneumatic muscles that ensure sufficient adaptability of the device to, for example, conduct patient exercise within the boundaries of pain supportability. Based on the research results, recommendations are offered for the optimum operation of the rehabilitation equipment. Full article
(This article belongs to the Special Issue Actuators and Robotic Devices for Rehabilitation and Assistance)
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25 pages, 6749 KiB  
Article
Application of Artificial Neuromolecular System in Robotic Arm Control to Assist Progressive Rehabilitation for Upper Extremity Stroke Patients
by Jong-Chen Chen and Hao-Ming Cheng
Actuators 2024, 13(9), 362; https://doi.org/10.3390/act13090362 - 16 Sep 2024
Viewed by 759
Abstract
Freedom of movement of the hands is the most desired hope of stroke patients. However, stroke recovery is a long, long road for many patients. If artificial intelligence can assist human arm movement, the possibility of stroke patients returning to normal hand movement [...] Read more.
Freedom of movement of the hands is the most desired hope of stroke patients. However, stroke recovery is a long, long road for many patients. If artificial intelligence can assist human arm movement, the possibility of stroke patients returning to normal hand movement might be significantly increased. This study uses the artificial neuromolecular system (ANM system) developed in our laboratory as the core of motion control, in an attempt to learn to control the mechanical arm to produce actions similar to human rehabilitation training and the transition between different activities. This research adopts two methods. The first is hypothetical exploration, the so-called “artificial world” simulation method. The detailed approach uses the V-REP (Virtual Robot Experimentation Platform) to conduct different experimental runs to capture relevant data. Our policy is to establish an action database systematically to a certain extent. From these data, we use the ANM system with self-organization and learning capabilities to develop the relationship between these actions and establish the possibility of conversion between different activities. The second method of this study is to use the data from a hospital in Toronto, Canada. Our experimental results show that the ANM system can continuously learn for problem-solving. In addition, our three experimental results of adaptive learning, transfer learning, and cross-task learning further confirm that the ANM system can use previously learned systems to complete the delivered tasks through autonomous learning (instead of learning from scratch). Full article
(This article belongs to the Special Issue Advanced Actuation, Intelligent Sensor and Precise Manipulation Technology in Human–Robot Interaction)
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15 pages, 4024 KiB  
Article
Research on Landing Dynamics of Foot-High Projectile Body for High-Precision Microgravity Simulation System
by Zhenhe Jia, Yuehua Li, Weijie Hou, Libin Zang, Qiang Han, Baoshan Zhao, Bin Gao, Haiteng Liu, Yuhan Chen, Yumin An and Huibo Zhang
Actuators 2024, 13(9), 361; https://doi.org/10.3390/act13090361 - 16 Sep 2024
Viewed by 524
Abstract
A high-precision ground microgravity simulation environment serves as the prerequisite and key to studying landing dynamics in microgravity environments. However, the microgravity level accuracy in traditional ground simulation tests is difficult to guarantee and fails to precisely depict the collision behavior of massive [...] Read more.
A high-precision ground microgravity simulation environment serves as the prerequisite and key to studying landing dynamics in microgravity environments. However, the microgravity level accuracy in traditional ground simulation tests is difficult to guarantee and fails to precisely depict the collision behavior of massive spacecraft. To solve such problems, this paper takes the microgravity simulation system based on quasi-zero stiffness (QZS) mechanism as the research object, and simulates a high-precision and high-level microgravity environment. Then, the collision contact force model of the planar foot and high elastic body rubber is established, the landing dynamics research under different microgravity environments is carried out, the influence of different microgravity environments on the landing behavior of large mass spacecraft is analyzed in depth, and ground microgravity simulation experiments are carried out. The results show that the microgravity simulation level reaches 10−4 g, the error of gravity compensation for each working condition is not more than 4.22%, and the error of sinking amount is not more than 4.61%, which verifies the superior compensation performance of the QZS mechanism and the accuracy of the dynamic model. Full article
(This article belongs to the Section Aircraft Actuators)
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21 pages, 9354 KiB  
Article
Research on Active Trailer Steering Control Strategy of Tractor Semitrailer under Medium-/High-Speed Conditions
by Yuxi Tang, Yingfeng Cai, Ze Liu, Xiaoqiang Sun, Long Chen, Hai Wang and Zhaozhi Dong
Actuators 2024, 13(9), 360; https://doi.org/10.3390/act13090360 - 16 Sep 2024
Viewed by 450
Abstract
The study proposes an active trailer steering control method for tractor semitrailers to promote the path tracking effect of the trailer portion as well as lateral stability during lane changing. Firstly, a simplified model of a tractor semitrailer is constructed, and the MAP [...] Read more.
The study proposes an active trailer steering control method for tractor semitrailers to promote the path tracking effect of the trailer portion as well as lateral stability during lane changing. Firstly, a simplified model of a tractor semitrailer is constructed, and the MAP map is formed based on the genetic algorithm for the identification of the key parameters, which improves the model’s accuracy. Then the tractor and trailer’s yaw rate and sideslip angle at CG are tracked as the control objective and the trailer angle distribution strategy is given. Then the LQR-based corner controller is designed to control the steering actuators of each axle of the trailer. Finally, the effectiveness of the designed control strategy is verified based on the Trucksim/Simulink joint simulation platform and the semi-physical HiL test platform. The simulation results show that the designed controller can effectively improve the path tracking effect of the tractor and the trailer, and at the same time, the lateral stability parameters of the tractor and the trailer are also significantly improved, which improves the driving stability of the tractor semitrailer. Full article
(This article belongs to the Special Issue Actuator Fault Diagnosis, State Detection and Fault Tolerant Control for Ground and Rail Vehicles)
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16 pages, 6658 KiB  
Article
Soft Robotic Honeycomb-Velcro Jamming Gripper Design
by Yu Cheng Chung, Wai Tuck Chow and Van Pho Nguyen
Actuators 2024, 13(9), 359; https://doi.org/10.3390/act13090359 - 16 Sep 2024
Viewed by 641
Abstract
In this paper, using a honeycomb-velcro structure to generate a novel jamming gripper is explored. Each finger of the gripper consists of multi-layers with a honeycomb sandwich structure acting as a core wrapped by a fabric sheet and sealed by a latex membrane. [...] Read more.
In this paper, using a honeycomb-velcro structure to generate a novel jamming gripper is explored. Each finger of the gripper consists of multi-layers with a honeycomb sandwich structure acting as a core wrapped by a fabric sheet and sealed by a latex membrane. This structure can transit between unjammed (flexible) and jammed (rigid) states thanks to the vacuum pressure. Various materials of honeycomb structure, fabric, and reinforcements are investigated to seek optimal combinations for making the jamming fingers. Then, such fingers are deployed in experiments to evaluate the stiffness and the surface friction with different loads in terms of with or without vacuum. Vacuum pressure boosts the stiffness and friction of all the jamming fingers compared with the without-vacuum case. Attached to a gripper, the jamming finger shows good performance in diverse manipulation with food, a metal component, a toy, a can, and a bottle. Furthermore, the variable-stiffness finger under vacuum pressure can be utilized to perform assembly and installation operations such as pushing a bolt into an aligned hole. Full article
(This article belongs to the Special Issue Advancement in the Design and Control of Robotic Grippers)
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27 pages, 1772 KiB  
Article
Association Model-Based Intermittent Connection Fault Diagnosis for Controller Area Networks
by Longkai Wang, Shuqi Hu and Yong Lei
Actuators 2024, 13(9), 358; https://doi.org/10.3390/act13090358 - 14 Sep 2024
Viewed by 470
Abstract
Controller Area Networks (CANs) play an important role in many safety-critical industrial systems, which places high demands on their reliability performance. However, the intermittent connection (IC) of network cables, a random and transient connectivity problem, is a common but hard troubleshooting fault that [...] Read more.
Controller Area Networks (CANs) play an important role in many safety-critical industrial systems, which places high demands on their reliability performance. However, the intermittent connection (IC) of network cables, a random and transient connectivity problem, is a common but hard troubleshooting fault that can cause network performance degradation, system-level failures, and even safety issues. Therefore, to ensure the reliability of CANs, a fault symptom association model-based IC fault diagnosis method is proposed. Firstly, the symptoms are defined by examining the error records, and the domains of the symptoms are derived to represent the causal relationship between the fault locations and the symptoms. Secondly, the fault probability for each location is calculated by minimizing the difference between the symptom probabilities calculated from the count information and those fitted by the total probability formula. Then, the fault symptom association model is designed to synthesize the causal and the probabilistic diagnostic information. Finally, a model-based maximal contribution diagnosis algorithm is developed to locate the IC faults. Experimental results of three case studies show that the proposed method can accurately and efficiently identify various IC fault location scenarios in networks. Full article
(This article belongs to the Section Control Systems)
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36 pages, 9780 KiB  
Article
Multivariate Prediction Soft Sensor Model for Truck Cranes Based on Graph Convolutional Network and Random Forest
by Shengfei Ji, Wei Li, Bo Zhang, Wen Ji, Yong Wang and See-Kiong Ng
Actuators 2024, 13(9), 357; https://doi.org/10.3390/act13090357 - 12 Sep 2024
Viewed by 587
Abstract
Truck cranes, which are crucial construction equipment, need to maintain good operational performance to ensure safe use. However, the complex and ever-changing working conditions they face often make it challenging to test their performance effectively. To address this issue, a multi-input and multi-output [...] Read more.
Truck cranes, which are crucial construction equipment, need to maintain good operational performance to ensure safe use. However, the complex and ever-changing working conditions they face often make it challenging to test their performance effectively. To address this issue, a multi-input and multi-output soft sensor technology model is suggested, utilizing a graph convolutional network and random forest to predict key performance indicators of crane operations such as luffing, telescoping, winching, and slewing under varying conditions. This method aims to streamline the process of testing and debugging truck cranes, ultimately reducing time and costs. Initially, the graph convolutional network model is employed to extract relevant feature information linked to the target variable. Subsequently, using this feature information and the RF model, multiple decision trees are constructed for regression prediction of the target variables. An operational dataset reflecting the crane’s actual working conditions is then generated to assess the graph convolutional network and random forest model. The effectiveness of this approach is further confirmed through comparisons with other methods like gradient boosting trees, support vector regression, and multi-layer perceptron. Full article
(This article belongs to the Section High Torque/Power Density Actuators)
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18 pages, 9753 KiB  
Article
Research on Vibration Reduction Characteristics of High-Speed Elevator with Rolling Guide Shoes Based on Hydraulic Damping Actuator
by Dongming Hu, Qibing Wang and Jianming Zhan
Actuators 2024, 13(9), 356; https://doi.org/10.3390/act13090356 - 12 Sep 2024
Viewed by 589
Abstract
This paper endeavors to tackle the issue of horizontal vibrations encountered in high-speed and ultra-high-speed elevator cabins during operation. Given the limitations of traditional passive-control guide shoes in effectively mitigating these vibrations and the complexity and cost associated with active control systems, a [...] Read more.
This paper endeavors to tackle the issue of horizontal vibrations encountered in high-speed and ultra-high-speed elevator cabins during operation. Given the limitations of traditional passive-control guide shoes in effectively mitigating these vibrations and the complexity and cost associated with active control systems, a novel approach involving passive-control rolling guide shoes (PCRGS) integrated with hydraulic damping is explored. The PCRGS incorporates a hydraulic actuator and hydraulic damping, which can be modeled by a mechanical and hydraulic co-simulation model using AMESim2020 software. The simulation reveals a substantial reduction in cabin vibrations equipped with PCRGS. Specifically, under pulse excitation, the reduction ranges from 26.2% to 27.5%; under white noise excitation, it varies between 14.3% and 17.1%; and under sine wave excitation, the reduction spans 21.2% to 24.1%. Notably, the system meets the stringent ‘Excellent’ (<=0.07 m/s2) performance criteria under sine wave excitation at lower frequencies, signifying its high effectiveness. These findings not only underscore the potential of hydraulic passive-control guide shoes in mitigating elevator vibrations but also provide invaluable guidance for their further development and refinement. Full article
(This article belongs to the Special Issue Intelligent and Precision Control for Mechatronic/Electro-Hydraulic Systems)
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14 pages, 3525 KiB  
Article
Restoring Model of a Pneumatic Artificial Muscle with Structure Parameters: Analysis and Identification
by Minh Ky Nguyen, Van Chon Trinh, Ngoc Yen Phuong Vo and Thanh Danh Le
Actuators 2024, 13(9), 355; https://doi.org/10.3390/act13090355 - 12 Sep 2024
Viewed by 465
Abstract
This paper will develop the restoring model of a commercial pneumatic artificial muscle (PAM) based on a McKibben structure, which comprises an elastic element connected with a viscoelastic element in parallel. The elastic element is generated by compressed air inside the rubber bellow; [...] Read more.
This paper will develop the restoring model of a commercial pneumatic artificial muscle (PAM) based on a McKibben structure, which comprises an elastic element connected with a viscoelastic element in parallel. The elastic element is generated by compressed air inside the rubber bellow; meanwhile, the viscoelasticity is affected by the rubber material. In particular, the viscoelastic property of the rubber material is proposed based on the Maxwell model. Instead of derivative of integer orders, an equation of motion of the fractional model is introduced to better capture the amplitude- and frequency-dependent property of the viscoelasticity of the PAM. The equation expressing the hysteresis loop due to the viscoelasticity of the PAM material will then be analyzed and built. A water cycle algorithm is employed to determine the optimal set of the proposed model. To evaluate the effectiveness of the proposed model, a comparison between the simulation calculated from the proposed model and experimental data is considered under harmonic force excitation. This study’s results give potential insight into the field of system dynamic analysis with the elastic element being PAM. Full article
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23 pages, 40746 KiB  
Article
An Admittance Parameter Optimization Method Based on Reinforcement Learning for Robot Force Control
by Xiaoyi Hu, Gongping Liu, Peipei Ren, Bing Jia, Yiwen Liang, Longxi Li and Shilin Duan
Actuators 2024, 13(9), 354; https://doi.org/10.3390/act13090354 - 12 Sep 2024
Viewed by 628
Abstract
When a robot performs tasks such as assembly or human–robot interaction, it is inevitable for it to collide with the unknown environment, resulting in potential safety hazards. In order to improve the compliance of robots to cope with unknown environments and enhance their [...] Read more.
When a robot performs tasks such as assembly or human–robot interaction, it is inevitable for it to collide with the unknown environment, resulting in potential safety hazards. In order to improve the compliance of robots to cope with unknown environments and enhance their intelligence in contact force-sensitive tasks, this paper proposes an improved admittance force control method, which combines classical adaptive control and machine learning methods to make them use their respective advantages in different stages of training and, ultimately, achieve better performance. In addition, this paper proposes an improved Deep Deterministic Policy Gradient (DDPG)-based optimizer, which is combined with the Gaussian process (GP) model to optimize the admittance parameters. In order to verify the feasibility of the algorithm, simulations and experiments are carried out in MATLAB and on a UR10e robot, respectively. The experimental results show that the algorithm improves the convergence speed by 33% in comparison to the general model-free learning method, and has better control performance and robustness. Finally, the adjustment time required by the algorithm is 44% shorter than that of classical adaptive admittance control. Full article
(This article belongs to the Section Actuators for Robotics)
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13 pages, 25407 KiB  
Article
Mechanical Design of a New Hybrid 3R-DoF Bioinspired Robotic Fin Based on Kinematics Modeling and Analysis
by Eliseo de J. Cortés Torres, Luis E. García Gonzales, Luis E. Villamizar Marin and Cecilia E. García Cena
Actuators 2024, 13(9), 353; https://doi.org/10.3390/act13090353 - 11 Sep 2024
Viewed by 679
Abstract
The field of bioinspired underwater robots aims to replicate the capabilities of marine animals in artificial systems. Stingrays have emerged as highly promising species to be mimicked because of their flat body morphology and size. Furthermore, they are considered high-performance species due to [...] Read more.
The field of bioinspired underwater robots aims to replicate the capabilities of marine animals in artificial systems. Stingrays have emerged as highly promising species to be mimicked because of their flat body morphology and size. Furthermore, they are considered high-performance species due to their maneuverability, propulsion mode, and sliding efficiency. Designing and developing mechanisms to imitate their pectoral fins is a challenge for underwater robotic researchers mainly because the locomotion characteristics depend on the coordinated movement of the fins. In the state of the art, several mechanisms were proposed with 2 active rotation degrees of freedom (DoFs) to replicate fin movement. In this paper, we propose adding an additional active DoF in order to improve the realism in the robotic manta ray movement. Therefore, in this article, we present the mechanical design, modeling, and kinematics analysis of a 3-active-and-rotational-DoF pectoral fin inspired by the Mobula Alfredi or reef manta ray. Additionally, by using the kinematics model, we were able to simulate and compare the behaviour of both mechanisms, that is, those with 2 and 3 DoFs. Our simulation results reveal an improvement in the locomotion, and we hypothesized that with the third DoF, some specific missions, such as hovering or fast emergence to the surface, will have a better performance. Full article
(This article belongs to the Special Issue Bio-Inspired Soft Robotics)
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18 pages, 8956 KiB  
Article
Development and Experimental Study of a Mixed-Mode Vibration Isolator Using Magnetorheological Elastomer
by Qianjie Liu, Zhirong Guo, Wei Liu, Gang Li, Shengzhi Jin, Lei Yu and Guoliang Hu
Actuators 2024, 13(9), 352; https://doi.org/10.3390/act13090352 - 11 Sep 2024
Viewed by 476
Abstract
This paper proposes a mixed-mode (combining shear and squeeze working modes) vibration isolator using magnetorheological elastomer (MRE), which enables the isolator to have a larger working area and better isolation performance by combining the working modes of the MRE. Firstly, based on the [...] Read more.
This paper proposes a mixed-mode (combining shear and squeeze working modes) vibration isolator using magnetorheological elastomer (MRE), which enables the isolator to have a larger working area and better isolation performance by combining the working modes of the MRE. Firstly, based on the magnetorheological effect working principle of the MRE, the material selection and dimensional parameters of each component are determined through structural design and magnetic circuit calculation. On this basis, magnetic field simulation is conducted using Maxwell 16.0 software to analyze the distribution of magnetic field lines and magnetic induction in the working area. Simultaneously, equivalent stiffness and equivalent damping models are established to explore the variation of vibration response with external current and excitation frequency conditions. Finally, a vibration isolation experimental platform is built to test the mixed-mode MRE isolator. The experimental results are basically consistent with the simulation modeling results. The experimental results showed that when the external excitation is in the frequency range of 16 Hz, effective semi-active vibration isolation control could be achieved by applying different current inputs. The isolation effect of the system is difficult to effectively control using current input when the external excitation is at high frequency. These results validate the rationality and feasibility of the mixed-mode MRE isolator structure, which provides a good reference for the design of MRE isolators. Full article
(This article belongs to the Special Issue Magnetorheological Actuators and Dampers)
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14 pages, 6557 KiB  
Article
A Novel Design of Soft Corrugated Actuator for Creating Precise Head and Neck Positioning System
by Veysel Erel, Sanjana Suresh, Inderjeet Singh, Allison Palomino, Faiza Tafannum, Seyedehhelya Hosseini Nami, Steve Jiang, Hao Peng, Nicholas Gans and Muthu B. J. Wijesundara
Actuators 2024, 13(9), 351; https://doi.org/10.3390/act13090351 - 11 Sep 2024
Viewed by 891
Abstract
Soft robots are increasingly gaining popularity as a preferred choice for designing medical devices due to their inherently compliant and adaptable nature. As research continues to advance in this field, soft robots are poised to revolutionize healthcare by providing safer, more patient-centric solutions. [...] Read more.
Soft robots are increasingly gaining popularity as a preferred choice for designing medical devices due to their inherently compliant and adaptable nature. As research continues to advance in this field, soft robots are poised to revolutionize healthcare by providing safer, more patient-centric solutions. This paper presents the design of a novel soft corrugated actuator to create a system for positioning the head during head and neck cancer radiation therapy. Simulation and experimental data show that the presented actuator design can achieve linear expansion with respect to pressure in both free and under loading conditions. A machine learning model of the single actuator is created using experimental data (pressure, expansion, and weight) to predict the required pressure. The single actuator model’s validity is confirmed by using four actuators to achieve head flexion at a specific angle, illustrating its potential for implementation in a multi-actuator system. The preliminary design of the multi-actuator head and neck positioning system demonstrates its capability to achieve four degrees of freedom. Full article
(This article belongs to the Special Issue Actuators and Robots for Biomedical Applications)
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23 pages, 21925 KiB  
Article
Optimising Sodium Borohydride Reduction of Platinum onto Nafion-117 in the Electroless Plating of Ionic Polymer–Metal Composites
by Eyman Manaf, Daniel P. Fitzpatrick, Clement L. Higginbotham and John G. Lyons
Actuators 2024, 13(9), 350; https://doi.org/10.3390/act13090350 - 10 Sep 2024
Viewed by 476
Abstract
The effects of process parameters on the electroless plating of ionic polymer–metal composites (IPMCs) were studied in this work. Specifically, the NaBH4 reduction of platinum onto Nafion-117 was characterised. The effects of the concurrent variation of NaBH4 concentration, stir time and [...] Read more.
The effects of process parameters on the electroless plating of ionic polymer–metal composites (IPMCs) were studied in this work. Specifically, the NaBH4 reduction of platinum onto Nafion-117 was characterised. The effects of the concurrent variation of NaBH4 concentration, stir time and temperature on surface resistance were studied through a full factorial design. The three-factor three-level factorial design resulted in 27 runs. Surface resistance was measured using a four-point probe. A regression model with an R2 value of 97.45% was obtained. Surface resistance was found to decrease with increasing stir time (20 to 60 min) and temperature (20 to 60 °C). These responses were attributed to increased platinisation rates, resulting in more uniform electrode deposition, confirmed by scanning electron microscopy (SEM) and energy-dispersive X-ray (EDAX) analysis. Surface resistance decreased, going from 1% to 5% NaBH4 concentration, but increased from 5% to 10% concentration. This behaviour was attributed to surface morphology: increased grain size inducing porous electrodes, in line with findings in the literature. The maximum tip displacement, measured through a computer vision system, as well as the maximum blocking force, measured through an analytical balance setup, were obtained for all 27 samples. The varying results were discussed with regards to surface and cross-sectional SEMs, alongside EDAX analysis. Full article
(This article belongs to the Special Issue Electroactive Polymer (EAP) for Actuators and Sensors Applications)
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