Search Results (24)

In complex marine environments, ramp-based recovery systems for autonomous underwater vehicles (AUVs) often encounter engineering challenges such as reduced docking accuracy and success rate due to disturbances in the capture window attitude. In this study, a desktop-scale physical experimental platform for recovery compensation was designed and constructed. The system integrates attitude feedback provided by an attitude sensor and dual-motor actuation to achieve active roll and pitch compensation of the capture window. Based on the structural and geometric characteristics of the platform, a dual-channel closed-loop control strategy was proposed utilizing midpoint tracking of the capture window, accompanied by multi-level software limit protection and automatic centering mechanisms. The control algorithm was implemented using a discrete-time PID structure, with gain parameters optimized through experimental tuning under repeatable disturbance conditions. A first-order system approximation was adopted to model the actuator dynamics. Experiments were conducted under various disturbance scenarios and multiple control parameter configurations to evaluate the attitude tracking performance, dynamic response, and repeatability of the system. The results show that, compared to the uncompensated case, the proposed compensation mechanism reduces the $MSE$ by up to 76.4% and the $MaxAE$ by 73.5%, significantly improving the tracking accuracy and dynamic stability of the recovery window. The study also discusses the platform’s limitations and future optimization directions, providing theoretical and engineering references for practical AUV recovery operations. Full article

LiDAR-assisted wind turbine control holds strong potential for reducing structural loads and improving rotor speed regulation, thereby contributing to more sustainable wind energy generation. However, key research gaps remain: (i) the practical limitations of commercially available fixed beam LiDARs for large turbines, and (ii) the performance assessment of commonly used LiDAR assisted feedforward control methods. This study addresses these gaps by (i) analysing how the coherence of LiDAR estimated rotor effective wind speed is influenced by the number of beams, measurement locations, and turbulence box resolution, and (ii) comparing two established control strategies. Numerical simulations show that applying a low cut-off frequency in the low-pass filter can impair preview time compensation. This is particularly critical for large turbines, where reduced coherence due to fewer beams undermines the effectiveness of LiDAR assisted control compared to the smaller turbines. The subsequent evaluation of control strategies shows that the Schlipf method offers greater robustness and consistent load reduction, regardless of the feedback control design. In contrast, the Bossanyi method, which uses the current blade pitch measurements, performs well when paired with carefully tuned baseline controllers. However, using the actual pitch angle in the feedforward pitch rate calculation can lead to increased excitation at certain frequencies, particularly if the feedback controller is not well tuned to avoid dynamics in those ranges. Full article

We developed a multi-feature drowsiness detection model employing eye aspect ratio (EAR), mouth aspect ratio (MAR), head pose angles (yaw, pitch, and roll), and a Raspberry Pi 4 for real-time applications. The model was trained on the NTHU-DDD dataset and optimized using long short-term memory (LSTM) deep learning algorithms implemented using TensorFlow version 2.14.0. The model enabled robust drowsiness detection at a rate of 10 frames per second (FPS). The system embedded with the model was constructed for live image capture. The camera placement was adjusted for optimal positioning in the system. Various features were determined under diverse conditions (day, night, and with and without glasses). After training, the model showed an accuracy of 95.23%, while the accuracy ranged from 91.81 to 95.82% in validation. In stationary and moving vehicles, the detection accuracy ranged between 51.85 and 85.71%. Single-feature configurations exhibited an accuracy of 51.85 to 72.22%, while in dual features, the accuracy ranged from 66.67 to 75%. An accuracy of 80.95 to 85.71% was attained with the integration of all features. Challenges in the drowsiness included diminished accuracy with MAR alone and delayed prediction during transitions from non-drowsy to drowsy status. These findings underscore the model’s applicability in detecting drowsiness while highlighting the necessity for refinement. Through algorithm optimization, dataset expansion, and the integration of additional features and feedback mechanisms, the model can be improved in terms of performance and reliability. Full article

This paper presents a method to design a parameter adaptive suspension controller to boost ride comfort and to reduce motion sickness. According to recently published papers, combined motions of a sprung mass (SPMS) along heave and pitch directions tend to make motion sickness severe. To reduce motion sickness, it is necessary to design a controller which can reduce the heave and pitch vibrations of a SPMS. To avoid full-state feedback which is very difficult to implement in a real vehicle, a static output feedback (SOF) control is chosen as a feedback structure. With the SOF structure, linear quadratic SOF and parameter adaptive controllers are designed. When designing parameter adaptive controllers, an extended Kalman filter (EKF), equivalent to recursive least square (RLS), is selected for parameter adaptation. To verify performance of the controllers, simulation is performed on vehicle simulation tool. From simulation responses, it is checked whether the proposed parameter adaptive controllers are effective or not and which is the best controller, with respect to ride comfort and motion sickness. Full article

Modern powertrain configurations for electric vehicles introduce the possibility to actuate the wheel directly by means of in-wheel motors. These machines enable stiffer and more efficient traction, with the possibility of introducing pitch motion control due to the intrinsic coupling between longitudinal, vertical, and pitch dynamics. This paper proposes a pitch rate attenuation control exploiting a Lyapunov function that attempts to cancel the pitch rate dynamics from the model. Unlike previous works, this pitch control is performed exclusively with the traction machine; it does not rely on controllable suspension systems. The controller formulation guarantees global stability of the vehicle. Furthermore, it considers the nonlinearity of the plant introduced by the dependency on the pitch angle. To facilitate the feedback of the road profile needed by the Lyapunov controller, two Kalman filters are included in the control law. This work implements the described strategy on a half car model. Simulations examine different speed and road conditions. It is demonstrated that the control strategy can blend longitudinal and pitch rate attenuation torque commands using a rear in-wheel motor, attaining a reduction of up to $41\%$ for chassis pitch rate and $36\%$ for pitch acceleration. Full article

This paper presents a method to design an active suspension controller for 8 × 8 armored combat vehicles, which is called corner damping control (CDC). It is assumed that the target vehicle with 8 × 8 drive mechanisms and 8 suspensions has active actuators on each suspension for vertical, roll and pitch motion control on a sprung mass. A state-space model with 22 state variables is derived from the target vehicle. With the state-space model, a linear quadratic (LQ) cost function is defined. The control objective is to reduce the vertical acceleration, pitch and roll angles of a sprung mass for ride comfort, durability and turret stabilization. To avoid full-state feedback of LQR, a static output feedback control (SOF) is selected as a control structure for CDC. The vertical velocity, roll and pitch rates of a sprung mass, and vertical velocities at each corner, are selected as a sensor output. With those sensor outputs and LQ cost function, four LQ SOF controllers are designed. To validate the effectiveness of the LQ SOF controllers, simulation is carried out on a vehicle simulation package. From the simulation results, it is shown that the proposed CDC with LQ SOF controllers with a much smaller number of sensor outputs and controller gains can reduce the vertical acceleration, pitch and roll angles of a sprung mass and, as a result, improve ride comfort, durability and turret stabilization. Full article

This paper presents a method to design a suspension controller with a human body model for ride comfort improvement and motion sickness mitigation. Generally, it has been known that the vertical acceleration of a sprung mass should be reduced for ride comfort. On the other hand, recent studies have shown that, combined, the vertical acceleration and pitch rate of a sprung mass are key factors that cause motion sickness. However, those variables have been considered with respect to the center of gravity of a sprung mass. For motion sickness mitigation, the vertical acceleration of a human head should be also considered. In this paper, the vertical accelerations and pitch rates of a sprung mass and a human head are controlled by a suspension controller for ride comfort improvement and motion sickness mitigation. For the controller design, a half-car and human body models are adopted. With those models, several types of static output feedback suspension controller are designed with linear quadratic optimal control methodology. To reduce the pitch rate of the sprung mass and the vertical acceleration of the head, a filtered-X LMS algorithm is adopted as an adaptive feedforward algorithm and combined with the static output feedback controllers. A frequency response analysis and simulation are performed with the designed controllers on vehicle simulation software, CarSim^®. From the simulation results, it is shown that the proposed controllers can effectively reduce the vertical accelerations and the pitch rate of the sprung mass and the human head. Full article

This paper examined how rotary force feedback in knobs can enhance control over musical techniques, focusing on both performance and user experience. To support our study, we developed the Bend-aid system, a web-based sequencer with pre-designed haptic modes for pitch modulation, integrated with TorqueTuner, a rotary haptic device that controls pitch through programmable haptic effects. Then, twenty musically trained participants evaluated three haptic modes (No-force feedback (No-FF), Spring, and Detent) by performing a vibrato mimicry task, rating their experience on a Likert scale, and providing qualitative feedback in post-experiment interviews. The study assessed objective performance metrics (Pitch Error and Pitch Deviation) and subjective user experience ratings (Comfort, Ease of Control, and Helpfulness) of each haptic mode. User experience results showed that participants found force feedback helpful. Performance results showed that the Detent mode significantly improved pitch accuracy and vibrato stability compared to No-FF, while the Spring mode did not show a similar improvement. Post-experiment interviews showed that preferences for Spring and Detent modes varied, and the applicants provided suggestions for future knob designs. These findings suggest that force feedback may enhance both control and the experience of control in rotary knobs, with potential applications for more nuanced control in DMIs. Full article

This paper presents a design method of a suspension controller with an adaptive feedforward algorithm for ride comfort enhancement and motion sickness mitigation. Recently, it was shown that motion sickness is caused by combined heave and pitch motions of a sprung mass within the range of 0.8 and 8 Hz. For this reason, it is necessary to design a suspension controller for the purpose of reducing the heave and pitch vibration of a sprung mass within this range. To represent the heave acceleration and the pitch rate of a sprung mass, a 4-DOF half-car model is adopted as a vehicle model. For easy implementation in a real vehicle, a static output feedback control is adopted instead of a full-state one. To reduce the heave acceleration of a sprung mass for ride comfort enhancement, a linear quadratic SOF controller is designed. To reduce the pitch rate of a sprung mass for motion sickness mitigation, a filtered-X LMS algorithm is applied. To validate the method, simulation on vehicle simulation software is conducted. From the simulation results, it is shown that the proposed method is effective for ride comfort enhancement and motion sickness mitigation. Full article

This paper presents a method to design a static output feedback active suspension controller for ride comfort improvement and motion sickness reduction in a real vehicle system. Full-state feedback controller has shown good performance for active suspension control. However, it requires a lot of states to be measured, which is very difficult in real vehicles. To avoid this problem, a static output feedback (SOF) controller is adopted in this paper. This controller requires only three sensor outputs, vertical velocity, roll and pitch rates, which are relatively easy to measure in real vehicles. Three types of SOF controller are proposed and optimized with linear quadratic optimal control and the simulation optimization method. Two of these controllers have only three gains to be tuned, which are much smaller than those of full-state feedback. To validate the performance of the proposed SOF controllers, a simulation is carried out on a vehicle simulation package. From the results, the proposed SOF controllers are quite good at improving ride comfort and reducing motion sickness. Full article

This paper presents a method for designing an active suspension controller for ride comfort enhancement and motion sickness mitigation. For this, it is necessary to design an active suspension controller, which aims to reduce the vertical acceleration and pitch rate of a sprung mass in a vehicle. A half-car vehicle model was selected. For the controller design, a static output feedback (SOF) control was selected instead of a full-state feedback control because it is hard to measure all state variables in real vehicles. With the available signals, three types of SOF controller were proposed. To determine the gains of the SOF controllers, a linear quadratic optimal control methodology and a simulation-based optimization method were adopted. To validate the proposed method, a simulation was carried out using vehicle simulation software. The simulation results show that the proposed method is quite effective for ride comfort enhancement and motion sickness mitigation. Full article

Due to physical limitations and safety requirements, the rate and amplitude of change in wind turbines’ pitch angle are limited, which will bring integral saturation problems to the control system. This leads to the deterioration of the pitch control system’s performance or even an instability problem. This paper designs an anti-windup robust pitch angle control strategy to deal with pitch rate constraint issue to enhance the safety of the control system. First, to facilitate controller design, a filtered tracking-error technique is employed to transform the nonaffine form into an affine one. Subsequently, a feedback robust controller based on an uncertainty and disturbance estimator (UDE) is developed to handle the model’s uncertainty and external disturbances. To address the issue of integral saturation in the pitch system and guarantee its safety, an elliptical bounded constraint is integrated into the designed UDE strategy. This bounded UDE controller can improve the stability of power generation quality, reducing the mechanical loads on components. Finally, the effectiveness of the proposed scheme is verified on the Wind Turbine Blockset platform in Matlab/Simulink. It can achieve better performance than traditional methods. Full article

Experimental results from the Floating Offshore-wind and Controls Advanced Laboratory (FOCAL) experimental program, which tested a performance-matched model of the IEA Wind 15 MW Reference Turbine on a 1:70 scale floating semisubmersible platform, are compared with OpenFAST simulations. Four experimental campaigns were performed, and data from the fourth campaign, which focused on wind and wave testing of the scaled floating wind turbine system, are considered. Simulations of wave-only, wind-only, and wind/wave environments are performed in OpenFAST, and results for key metrics are compared with the experiment. Performance of the real-time Reference OpenSource COntroller (ROSCO) in above-rated wind conditions, including the effects of the floating feedback loop, are investigated. Results show good agreement in mean values for key metrics, and hydrodynamic effects are matched well. Differences in the surge resonant behavior of the platform are identified and discussed. The effect of the controller and floating feedback loop is evident in both the experiment and OpenFAST, showing significant reduction in platform pitch response and tower base bending load near the platform pitch natural frequency. Full article

This study aims to develop dynamic co-simulation and control for analyzing the IEA 15 MW semi-submersible floating wind turbine under Taiwan offshore-wind-farm conditions of wind and wave. The IEA 15 MW wind turbine is mounted on a UMaine VolturnUS-S reference platform with a mooring system designed for a water depth of 70 m, in this study. The dynamic co-simulation combines software of SIMPACK, MATLAB/SIMULINK, AeroDyn, HydroDyn, WAMIT, and MAP++ to achieve the complex dynamic simulation of aerodynamics, hydrodynamics, mechanism dynamics and control system dynamics. In addition, this study proposes a novel power-control strategy combining fuzzy sliding-mode control with additional pitching-rate feedback. Since the motion of the floating platform, especially the pitching motion, contributes to power oscillation, the proposed novel power-control strategy with additional pitching-rate feedback can reduce the influence of the floating-platform oscillation motion, and is verified under different conditions. Full article

The development of the Light Detection and Ranging (LIDAR) technology has enabled wider options for wind turbine control, in particular regarding disturbance rejection. The LIDAR measurements provide a spatial, preview wind information, based on which the controller has a better chance to cope with the wind disturbance before it affects the turbine operation. In this paper, a model predictive controller for above-rated wind turbine control was developed with the use of pseudo-LIDAR wind measurements data. A predictive control algorithm was developed based on a linearised wind turbine model, in which the disturbance from the incoming wind was computed by the LIDAR simulator. The optimal control action was applied to the nonlinear turbine model. The developed controller was compared with the baseline control and a previously developed LIDAR-assisted control combining a feedback-and-feedforward design. Our simulation studies on a 5 MW nonlinear wind turbine model, under different wind conditions, demonstrated that the developed LIDAR-based predictive control achieved improved performance in the presence of small variations in the out-of-plane rotor torque and fore-aft tower acceleration, as well as a smoother generator speed regulation and satisfied pitch activity control constraints. Full article