Search Results (136)

This paper introduces a novel model-free fractional-order composite control methodology specifically designed for precision positioning in permanent magnet synchronous motor (PMSM) drives. The proposed framework ingeniously combines a composite control architecture, featuring a super twisting double fractional-order differential sliding mode controller (STDFDSMC) synergistically integrated with a complementary extended state observer (CESO). The STDFDSMC incorporates an innovative fractional-order double differential sliding mode surface, engineered to deliver superior robustness, enhanced flexibility, and accelerated convergence rates, while simultaneously addressing potential singularity issues. The CESO is implemented to achieve precise estimation and compensation of both intrinsic and extrinsic disturbances affecting PMSM drive systems. Through rigorous application of Lyapunov stability theory, we provide a comprehensive theoretical validation of the closed-loop system’s convergence stability under the proposed control paradigm. Extensive comparative analyses with conventional control methodologies are conducted to substantiate the efficacy of our approach. The comparative results conclusively demonstrate that the proposed control method represents a significant advancement in PMSM drive performance optimization, offering substantial improvements over existing control strategies. Full article

A new predefined time sliding mode control theme is proposed and applies to the multi-switch combination–combination synchronization (MSCCS) of fractional-order (FO) hyperchaotic systems. Firstly, based on the Lyapunov stability theory, we demonstrate the effectiveness of our proposed predefined time sliding mode control theme. Meanwhile, based on the new predefined time control strategy, we propose new sliding mode surfaces and controllers to achieve the MSCCS of FO hyperchaotic systems. Considering the system’s external environment’s complexity in practical applications, the parameter uncertainties and external disturbances are added to the FO hyperchaotic system. Through the final numerical simulation, the predefined time slide mode controller proposed in this paper can make the drive–response systems reach the predefined time synchronization, thus proving the effectiveness of the control strategy and its robustness to some unfavorable factors, such as external perturbations. Full article

In this paper, a novel fractional-order chaotic system equipped with symmetric attractors was proposed for the full-coverage path-planning problem of mobile robots, especially in application scenarios where path privacy needs to be protected. By coupling this system with a kinematic model of a mobile robot, a novel path-planning algorithm was designed to realize encrypted full-coverage path planning. A predefined time-synchronization control strategy effectively resolved inconsistencies in the path caused by initial position, time delay, and uncertain disturbances. Numerical simulation results demonstrated that the proposed path-planning method, based on the novel chaotic system, significantly improved coverage and randomness, compared to existing studies. Moreover, it maintained accuracy and stability in path planning, even in the presence of time delays and uncertain disturbances. Full article

A variable fractional-order (VFO) fuzzy sliding mode controller is designed to control the speed of a permanent magnet synchronous motor (PMSM). First, a VFO sliding mode surface is established. Then, a VFO fuzzy sliding mode controller is designed, capable of suppressing the effects of parameter uncertainties and disturbances to achieve precise PMSM speed control. The global stability and finite time convergence of the controlled system state are demonstrated using Lyapunov stability theory. The numerical and experimental results validate the effectiveness of the controller, showing better immunity to disturbances and a smaller overshoot compared to PID and fixed-order fuzzy sliding mode controllers. Full article

This paper investigates the attitude control problem of unmanned aerial vehicles (UAVs), especially in the presence of uncertainties and external disturbances. To address this challenge, a fractional-order reaching law sliding mode with active disturbance rejection controller (FOSM-ADRC) is proposed. The controller combines a fractional-order calculus operator and active disturbance rejection controller (ADRC) techniques to enhance the dynamic performance and robustness of the system. Through the inner and outer loop design, the jitter of the sliding mode controller (SMC) is effectively suppressed, and fast response and strong anti-jamming ability are achieved, which, in turn, improves the control accuracy. Firstly, the dynamic model of the UAV is established, and its nonlinear dynamic characteristics are analyzed in detail. On this basis, a fractional-order reaching law sliding mode controller (FO-SMC) is designed as the outer loop to achieve fast response. ADRC is employed in the inner loop to compensate for the internal and external disturbances of the system. The results show that the FOSM-ADRC can effectively suppress the jitter phenomenon and maintain good control performance. Full article

This paper has addressed the terrain-following problem of an autonomous underwater vehicle for widely used ocean survey missions. Considering the terrain feature description with limited sensing ability in underwater scenarios, a vertically installed multi-beam sonar and a downward single-beam echo sounder are equipped to obtain seafloor detecting data online, and a local polynomial fitting algorithm is carried out with a receding horizon strategy in order to generate a proper tracking path to keep the desired height above the sea bottom. With the construction of the autonomous underwater vehicle dynamic model in the North East Down frame regarding the vertical plane, an online sparse identification algorithm is implemented to obtain the model parameters during the diving process. Then, a fractional-order sliding mode controller is proposed to enable accurate tracking of the path planned and Lyapunov-based theory is utilized to prove the stability of the control algorithm. With the simulation results, the tracking effectiveness of the fractional-order sliding mode controller with in situ identification is verified. Full article

This paper introduces a novel adaptive control method for suspension vehicle systems in response to road disturbances. The considered model is based on an active symmetry quarter car (SQC) fractional order suspension system (FOSS). The word symmetry in SQC refers to the symmetry of the suspension system in the front tires or the rear tires of the car. The active suspension controller is generally driven by an external force like a hydraulic or pneumatic actuator. The external force of the actuator is determined using fractional dynamic sliding mode control (FDSMC) to counteract road disturbances and eliminate the chattering caused by sliding mode control (SMC). In FDSMC, a fractional integral acts as a low-pass filter before the system actuator to remove high-frequency chattering, necessitating an additional state for FDSMC implementation assuming all FOSS state variables are available but the parameters are unknown and uncertain. Hence, an adaptive procedure is proposed to estimate these parameters. To enhance closed-loop system performance, an adaptive proportional-integral (PI) procedure is also employed, resulting in the FDSMC-PI approach. A comparison is made between two SQC suspension system models, the fractional order suspension system (FOSS) and the integer order suspension system (IOSS). The IOSS controller is based on dynamic sliding mode control (DSMC) and a PI procedure (DSMC-PI). The results show that FDSMC outperforms DSMC. Full article

Electric vehicles demand efficient and robust motor control to maximize range and performance. This paper presents an innovative adaptive fractional-order sliding mode (FO-SM) control approach tailored for Direct Torque Control with Space Vector Modulation (DTC-SVM) applied to induction motor drives. This approach tackles the challenges of parameter variations inherent in real-world applications, such as temperature changes and load fluctuations. By leveraging the inherent robustness of FO-SM and the fast dynamic response of DTC-SVM, our proposed control strategy achieves superior performance, significantly reduced torque ripple, and improved efficiency. The adaptive nature of the control system allows for real-time adjustments based on system conditions, ensuring reliable operation even in the presence of uncertainties. This research presents a significant advancement in electric vehicle propulsion systems, offering a powerful and adaptable control solution for induction motor drives. Our findings demonstrate the potential of this innovative approach to enhance the robustness and performance of electric vehicles, paving the way for a more sustainable and efficient future of transportation. In fact, the paper proposes using an adaptive approach to control the electric vehicle’s speed based on the fractional calculus of sliding mode control. The adaptive algorithm converges to the actual values of all system parameters. Moreover, the obtained performance results are reached without precise system modeling. Full article

Taking a Vienna rectifier as the research object, the power mathematical model based on a switching function is established according to its working principle. A sliding mode variable structure control algorithm based on the reaching law is examined in order to address the issues of the slow response speed and inadequate anti-interference of classical PI control in the face of abrupt changes in the DC-side load. In response to the sluggish convergence rate and inadequate chattering suppression of classical integer order sliding mode control, a fractional order exponential reaching law sliding mode, direct power control approach with rapid convergence is developed. The fractional calculus is introduced into the sliding mode control, and the dynamic performance and convergence speed of the control system are improved by increasing the degree of freedom of the fractional calculus operator. The method of including a balance factor in the zero-sequence component is employed to address the issue of the midpoint potential equilibrium in the Vienna rectifier. Ultimately, the suggested control is evaluated against classical PI control through simulation analysis and experimental validation. The findings indicate that the proposed technique exhibits rapid convergence, reduced control duration, and enhanced robustness, hence augmenting its resistance to interference. Full article

This study investigates the dynamic behavior and vibration mitigation of a fractional single-degree-of-freedom (SDOF) viscoelastic shape memory alloy spring oscillator system subjected to harmonic external forces. A fractional derivative approach is employed to characterize the viscoelastic properties of shape memory alloy materials, leading to the development of a novel fractional viscoelastic model. The model is then theoretically examined using the averaging method, with its effectiveness being confirmed through numerical simulations. Furthermore, the impact of various parameters on the system’s low- and high-amplitude vibrations is explored through a visual response analysis. These findings offer valuable insights for applying fractional sliding mode control (SMC) theory to address the system’s vibration control challenges. Despite the high-amplitude vibrations induced by the fractional order, SMC effectively suppresses these vibrations in the shape memory alloy spring system, thereby minimizing the risk of catastrophic events. Full article

The state of charge (SoC) is a critical parameter in lithium-ion batteries and their alternatives. It determines the battery’s remaining energy capacity and influences its performance longevity. Accurate SoC estimation is essential for making informed charging and discharging decisions, mitigating the risks of overcharging or deep discharge, and ensuring safety. Battery management systems rely on SoC estimation, utilising both hardware and software components to maintain safe and efficient battery operation. Existing SoC estimation methods are broadly classified into direct and indirect approaches. Direct methods (e.g., Coulumb counting) rely on current measurements. In contrast, indirect methods (often based on a filter or observer) utilise a model of a battery to incorporate voltage measurements besides the current. While the latter is more accurate, it faces challenges related to sensor drift, computational complexity, and model inaccuracies. The need for more precise and robust SoC estimation without increasing complexity is critical, particularly for real-time applications. Recently, sliding mode observers (SMOs) have gained prominence in this field for their robustness against model uncertainties and external disturbances, offering fast convergence and superior accuracy. Due to increased interest, this review focuses on various SMO approaches for SoC estimation, including first-order, adaptive, high-order, terminal, fractional-order, and advanced SMOs, along with hybrid methods integrating intelligent techniques. By evaluating these methodologies, their strengths, weaknesses, and modelling frameworks in the literature, this paper highlights the ongoing challenges and future directions in SoC estimation research. Unlike common review papers, this work also compares the performance of various existing methods via a comprehensive simulation study in MATLAB 2024b to quantify the difference and guide the users in selecting a suitable version for the applications. Full article

During the hoisting and lowering operations of a tower crane, dynamic variations in cable lengths significantly influence the oscillation frequency and amplitude of the load. These variations complicate the oscillation characteristics, heightening the challenge of balancing obstacle avoidance with precise positioning. To tackle this issue, we propose a trajectory planning and tracking control method that integrates hoisting control to reduce the impact of varying cable lengths on load swinging and achieve accurate positioning during obstacle navigation. A novel definition of swing angle is introduced to model the crane’s rigid and swinging components separately, enhancing model accuracy while simplifying complexity. A piecewise polynomial constructs the load trajectory in a low-dimensional flat space, which is then mapped to a high-dimensional generalized state space through a homeomorphic transformation, ensuring trajectory smoothness and traceability. A fractional-order sliding mode controller is employed to facilitate rapid and precise tracking of the actuated degrees of freedom, suppressing load oscillation while maintaining positioning accuracy. Experimental validation on a tower crane platform shows that the proposed strategy enables smooth obstacle avoidance and precise target point reaching, even with varying cable lengths. Full article

For elevators, appropriate speed control is pivotal for ensuring the safety and comfort of passengers and optimizing energy efficiency, system stability, and service life. Therefore, the design and implementation of effective speed control strategies are crucial for the operation and management of modern elevator systems. In response to this issue, this paper establishes a dynamic model of an elevator through mechanism analysis. Then, a novel fractional-order sliding mode control strategy with the assistance of a fixed-time adaptive sliding mode observer is proposed. The designed observer can effectively monitor and counteract external perturbations, thereby enhancing the stability and precision of the control system. The fractional-order sliding mode controller can realize a fixed-time convergence property, which is rigorously proven in the sense of Lyapunov. Finally, the effectiveness and superiority of the control scheme are validated by simulations compared with benchmark controllers. Full article

In this study, a comparative analysis of three different control methods for precise, real-time control of a complex dynamic double-tank liquid level process system was performed. Since the system in question has a time-delayed structure, feedforward proportional integral (FF-PI) control and cascaded nonlinear feedforward proportional integral delayed (CNPIR) controllers were tested on the process system. While the FF-PI controller improved the response time of the system, it showed limitations in handling external disturbances and nonlinearities. On the other hand, the CNPIR controller showed better improvements in control accuracy and lower overshoot compared to the FF-PI controller. Since the process system has a nonlinear model and is affected by external disturbances, these two controllers were inadequate in this study when compared to the fractional order adaptive proportional integral derivative sliding mode controller (FO-APIDSMC). The FO-APIDSMC controller provided fairly good performance in both tracking accuracy and disturbance rejection control for non-chattering, fast finite-time convergence, increased robustness, and uncertain dynamic processes. Experimental results reveal that the FO-APIDSMC controller achieves superior minimized tracking error and outperforms the FF-PI and CNPIR controllers by effectively handling uncertainties and external disturbances. Full article

Industrial mobile robots easily experience actuator loss of some effectiveness and additive bias faults due to the working scenarios, resulting in unexpected performance degradation. This article proposes a novel adaptive fault-tolerant control (FTC) strategy for nonholonomic mobile robot systems subject to simultaneous actuator lock-in-place (LIP) and partial loss-of-effectiveness (LOE) faults. First, a nominal fractional-order sliding mode controller based on the designed exponential super-twisting reaching law is investigated to reduce the reaching phase time and eliminate the chattering. To address the time-varying LIP faults and uncertainties, a novel barrier function (BF)-based gain is explored to assist the super-twisting law. An estimator is designed to estimate the lower bound of the time-varying partial LOE fault coefficients, thus without requiring the boundary information of faults that is commonly requested in traditional FTC schemes. Combined with the nominal controller clubbed with BF and estimator-based LOE fault compensation term, the fault-tolerant controller is finally constructed. The proposed FTC scheme achieves fast convergence and the sliding variables can be confined in a predetermined neighborhood of the sliding manifold under actuator faults. The results show that the proposed controller has superior tracking performance under faulty conditions compared with other state-of-the-art adaptive FTC approaches. Full article