Pressure ripples in electric power steering （EPS） systems can be caused by the phase lag between the driver s steering torque and steer angle, the nonlinear frictions, and the disturbances from road and sensor noise...Pressure ripples in electric power steering （EPS） systems can be caused by the phase lag between the driver s steering torque and steer angle, the nonlinear frictions, and the disturbances from road and sensor noise especially during high-frequency maneuvers. This paper investigates the use of the robust fuzzy control method for actively reducing pressure ripples for EPS systems. Remarkable progress on steering maneuverability is achieved. The EPS dynamics is described with an eight-order nonlinear state-space model and approximated by a Takagi-Sugeno （T-S） fuzzy model with time-varying delays and external disturbances. A stabilization approach is then presented for nonlinear time-delay systems through fuzzy state feedback controller in parallel distributed compensation （PDC） structure. The closed-loop stability conditions of EPS system with the fuzzy controller are parameterized in terms of the linear matrix inequality （LMI） problem. Simulations and experiments using the proposed robust fuzzy controller and traditional PID controller have been carried out for EPS systems. Both the simulation and experiment results show that the proposed fuzzy controller can reduce the torque ripples and allow us to have a good steering feeling and stable driving.展开更多
Current research on lane-keeping systems ignores the effect of the driver and external resistance on the accuracy of tracking the lane centerline.To reduce the lateral deviation of the vehicle,a lane-keeping control m...Current research on lane-keeping systems ignores the effect of the driver and external resistance on the accuracy of tracking the lane centerline.To reduce the lateral deviation of the vehicle,a lane-keeping control method based on the fuzzy Takagi-Sugeno(T-S)model is proposed.The method adopts a driver model based on near and far visual angles,and a driver-road-vehicle closed-loop model based on longitudinal nonlinear velocity variation,obtaining the expected assist torque with a robust H∞controller which is designed based on parallel distributed compensation and linear matrix inequality.Considering the external influences of tire adhesion and aligning torque when the vehicle is steering,a feedforward compensation control is designed.The electric power steering system is adopted as the actuator for lane-keeping,and active steering redressing is realized by a control motor.Simulation results based on Carsim/Simulink and real vehicle test results demonstrate that the method helps to maintain the vehicle in the lane centerline and ensures driving safety.展开更多
This paper proposes a TSK fuzzy approach to channel estimation for Orthogonal Frequency Division Multiplexing （OFDM） systems. The information of dispersive fading channel is described by using TSK fuzzy model, which...This paper proposes a TSK fuzzy approach to channel estimation for Orthogonal Frequency Division Multiplexing （OFDM） systems. The information of dispersive fading channel is described by using TSK fuzzy model, which is updated by the pilot symbols. The proposed approach can trace the variation of channel and it is computationally simple. Its performance is tested via simulations. Results show that it is comparable to that of ideal Minimum Mean-Square-Error （MMSE） method, especially at the low Signal to Noise Ratio （SNR）.展开更多
A new approach is provided to estimate the state of arbitrarily maneuvering target. In this approach a fuzzy compensator is used to tackle the uncertainty which results from the targets arbitrarily maneuvering. To des...A new approach is provided to estimate the state of arbitrarily maneuvering target. In this approach a fuzzy compensator is used to tackle the uncertainty which results from the targets arbitrarily maneuvering. To design the observer of the nonlinear system, the fuzzy T S model and the receding horizon control strategy are employed. Besides, the design depends on tracking the output error of the model. Compared with the technique used in other articles, the errors between the first estimated value and the true state value of the estimated variable are not strictly required. Numerical simulating results show that the proposed approach can estimate the states of the random maneuvering targets on line so as to obtain the exact tracking of the target.展开更多
基金supported Foundation of National Development and Reform Commission of China (No. 2040)
文摘Pressure ripples in electric power steering （EPS） systems can be caused by the phase lag between the driver s steering torque and steer angle, the nonlinear frictions, and the disturbances from road and sensor noise especially during high-frequency maneuvers. This paper investigates the use of the robust fuzzy control method for actively reducing pressure ripples for EPS systems. Remarkable progress on steering maneuverability is achieved. The EPS dynamics is described with an eight-order nonlinear state-space model and approximated by a Takagi-Sugeno （T-S） fuzzy model with time-varying delays and external disturbances. A stabilization approach is then presented for nonlinear time-delay systems through fuzzy state feedback controller in parallel distributed compensation （PDC） structure. The closed-loop stability conditions of EPS system with the fuzzy controller are parameterized in terms of the linear matrix inequality （LMI） problem. Simulations and experiments using the proposed robust fuzzy controller and traditional PID controller have been carried out for EPS systems. Both the simulation and experiment results show that the proposed fuzzy controller can reduce the torque ripples and allow us to have a good steering feeling and stable driving.
基金National Natural Science Foundation of China(Grant Nos.51675151,U1564201)Open Fund of the Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment of Ministry of Education(Grant No.GDSC202013).
文摘Current research on lane-keeping systems ignores the effect of the driver and external resistance on the accuracy of tracking the lane centerline.To reduce the lateral deviation of the vehicle,a lane-keeping control method based on the fuzzy Takagi-Sugeno(T-S)model is proposed.The method adopts a driver model based on near and far visual angles,and a driver-road-vehicle closed-loop model based on longitudinal nonlinear velocity variation,obtaining the expected assist torque with a robust H∞controller which is designed based on parallel distributed compensation and linear matrix inequality.Considering the external influences of tire adhesion and aligning torque when the vehicle is steering,a feedforward compensation control is designed.The electric power steering system is adopted as the actuator for lane-keeping,and active steering redressing is realized by a control motor.Simulation results based on Carsim/Simulink and real vehicle test results demonstrate that the method helps to maintain the vehicle in the lane centerline and ensures driving safety.
文摘This paper proposes a TSK fuzzy approach to channel estimation for Orthogonal Frequency Division Multiplexing （OFDM） systems. The information of dispersive fading channel is described by using TSK fuzzy model, which is updated by the pilot symbols. The proposed approach can trace the variation of channel and it is computationally simple. Its performance is tested via simulations. Results show that it is comparable to that of ideal Minimum Mean-Square-Error （MMSE） method, especially at the low Signal to Noise Ratio （SNR）.
文摘A new approach is provided to estimate the state of arbitrarily maneuvering target. In this approach a fuzzy compensator is used to tackle the uncertainty which results from the targets arbitrarily maneuvering. To design the observer of the nonlinear system, the fuzzy T S model and the receding horizon control strategy are employed. Besides, the design depends on tracking the output error of the model. Compared with the technique used in other articles, the errors between the first estimated value and the true state value of the estimated variable are not strictly required. Numerical simulating results show that the proposed approach can estimate the states of the random maneuvering targets on line so as to obtain the exact tracking of the target.
