This paper investigates the problem of path tracking control for autonomous ground vehicles(AGVs),where the input saturation,system nonlinearities and uncertainties are considered.Firstly,the nonlinear path tracking s...This paper investigates the problem of path tracking control for autonomous ground vehicles(AGVs),where the input saturation,system nonlinearities and uncertainties are considered.Firstly,the nonlinear path tracking system is formulated as a linear parameter varying(LPV)model where the variation of vehicle velocity is taken into account.Secondly,considering the noise effects on the measurement of lateral offset and heading angle,an observer-based control strategy is proposed,and by analyzing the frequency domain characteristics of the derivative of desired heading angle,a finite frequency H_∞index is proposed to attenuate the effects of the derivative of desired heading angle on path tracking error.Thirdly,sufficient conditions are derived to guarantee robust H_∞performance of the path tracking system,and the calculation of observer and controller gains is converted into solving a convex optimization problem.Finally,simulation examples verify the advantages of the control method proposed in this paper.展开更多
Parking difficulties have become a social issue that people have to solve.Automated parking system is practicable for quick par operations without a driver which can also greatly reduces the probability of parking acc...Parking difficulties have become a social issue that people have to solve.Automated parking system is practicable for quick par operations without a driver which can also greatly reduces the probability of parking accidents.The paper proposes a Lyapunov-based nonlinear model predictive controller embedding an instructable solution which is generated by the modified rear-wheel feedback method(RF-LNMPC)in order to improve the overall path tracking accuracy in parking conditions.Firstly,A discrete-time RF-LNMPC considering the position and attitude of the parking vehicle is proposed to increase the success rate of automated parking effectively.Secondly,the RF-LNMPC problem with a multi-objective cost function is solved by the Interior-Point Optimization,of which the iterative initial values are described as the instructable solutions calculated by combining modified rear-wheel feedback to improve the performance of local optimal solution.Thirdly,the details on the computation of the terminal constraint and terminal cost for the linear time-varying case is presented.The closed-loop stability is verified via Lyapunov techniques by considering the terminal constraint and terminal cost theoretically.Finally,the proposed RF-LNMPC is implemented on a selfdriving Lincoln MKZ platform and the experiment results have shown improved performance in parallel and vertical parking conditions.The Monte Carlo analysis also demonstrates good stability and repeatability of the proposed method which can be applied in practical use in the near future.展开更多
Path tracking performed by multiple chassis actuators remains a significant yet challenging issue in intelligent vehicles.This paper presents a robust optimal path tracking control for intelligent vehicles equipped wi...Path tracking performed by multiple chassis actuators remains a significant yet challenging issue in intelligent vehicles.This paper presents a robust optimal path tracking control for intelligent vehicles equipped with a novel wheel module.A wheel module,named corner drive system(CDS),is proposed by integrating drive,brake,steering,and suspension subsystems.In light of the multi-actuator-integrate characteristic of the CDS,a reconfigurable concept is adopted to carry out the vehicle dynamics modeling.To realize an invariance system for both parametric and nonparametric uncertainties,an integral sliding mode control(ISMC)scheme is devised for desired path tracking by combining the advantages of linear quadratic regulator(LQR)in optimization and SMC in robustness.The chattering problem of the ISMC is analyzed and two continuous controllers for chattering elimination are proposed.A control allocation strategy is proposed to dynamically assign the virtual inputs generated by ISMC among four wheels to optimize vehicle stability and minimize energy dissipation.The superiority of the proposed control scheme is demonstrated under different chassis layouts,road friction conditions,and benchmark controllers on a CarSim-based high-fidelity vehicle model with simulation comparison.Subsequently,the Hardware-in-the-Loop(HiL)test is carried out to further evaluate the feasibility and real-time control performance.The quantitative results demonstrate the path tracking performance of the proposed robust optimal controller under both parametric and nonparametric uncertainties.展开更多
A fuzzy robust path tracking strategy of an active pelagic trawl system with ship and winch regulation is proposed.First,nonlinear mathematic model of the pelagic trawl system was derived using Lagrange equation and f...A fuzzy robust path tracking strategy of an active pelagic trawl system with ship and winch regulation is proposed.First,nonlinear mathematic model of the pelagic trawl system was derived using Lagrange equation and further simplified as a low order model for the convenience of controller design.Then,an active path tracking strategy of pelagic trawl system was investigated to improve the catching efficiency of the target fish near the sea bottom.By means of the active tracking control,the pelagic trawl net can be positioned dynamically to follow a specified trajectory via the coordinated winch and ship regulation.In addition,considering the system nonlinearities,modeling uncertainties and the unknown exogenous disturbance of the trawl system model,a nonlinear robust H2 /H∞ controller based on Takagi-Sugeno(T-S) fuzzy model was presented,and the simulation comparison with linear robust H2 /H∞ controller and PID method was conducted for the validation of the nonlinear fuzzy robust controller.The nonlinear simulation results show that the average tracking error is 0.4 m for the fuzzy robust H2 /H∞ control and 125.8 m for the vertical and horizontal displacement,respectively,which is much smaller than linear H2 /H∞ controller and the PID controller.The investigation results illustrate that the fuzzy robust controller is effective for the active path tracking control of the pelagic trawl system.展开更多
基金supported by the National Natural Science Foundation of China(62173029,62273033,U20A20225)the Fundamental Research Funds for the Central Universities,China(FRF-BD-19-002A)。
文摘This paper investigates the problem of path tracking control for autonomous ground vehicles(AGVs),where the input saturation,system nonlinearities and uncertainties are considered.Firstly,the nonlinear path tracking system is formulated as a linear parameter varying(LPV)model where the variation of vehicle velocity is taken into account.Secondly,considering the noise effects on the measurement of lateral offset and heading angle,an observer-based control strategy is proposed,and by analyzing the frequency domain characteristics of the derivative of desired heading angle,a finite frequency H_∞index is proposed to attenuate the effects of the derivative of desired heading angle on path tracking error.Thirdly,sufficient conditions are derived to guarantee robust H_∞performance of the path tracking system,and the calculation of observer and controller gains is converted into solving a convex optimization problem.Finally,simulation examples verify the advantages of the control method proposed in this paper.
基金Supported by National Key R&D Program of China (Grant No.2021YFB2501800)National Natural Science Foundation of China (Grant No.52172384)+1 种基金Science and Technology Innovation Program of Hunan Province of China (Grant No.2021RC3048)State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle of China (Grant No.72275004)。
文摘Parking difficulties have become a social issue that people have to solve.Automated parking system is practicable for quick par operations without a driver which can also greatly reduces the probability of parking accidents.The paper proposes a Lyapunov-based nonlinear model predictive controller embedding an instructable solution which is generated by the modified rear-wheel feedback method(RF-LNMPC)in order to improve the overall path tracking accuracy in parking conditions.Firstly,A discrete-time RF-LNMPC considering the position and attitude of the parking vehicle is proposed to increase the success rate of automated parking effectively.Secondly,the RF-LNMPC problem with a multi-objective cost function is solved by the Interior-Point Optimization,of which the iterative initial values are described as the instructable solutions calculated by combining modified rear-wheel feedback to improve the performance of local optimal solution.Thirdly,the details on the computation of the terminal constraint and terminal cost for the linear time-varying case is presented.The closed-loop stability is verified via Lyapunov techniques by considering the terminal constraint and terminal cost theoretically.Finally,the proposed RF-LNMPC is implemented on a selfdriving Lincoln MKZ platform and the experiment results have shown improved performance in parallel and vertical parking conditions.The Monte Carlo analysis also demonstrates good stability and repeatability of the proposed method which can be applied in practical use in the near future.
基金supported by the“Beijing Natural Science Foundation”under Grant L233039“Pioneer and Leading Goose R&D Program of Zhejiang”under Grant 2023C01133“Key R&D Program of Ningbo”under Grant 2023Z014.
文摘Path tracking performed by multiple chassis actuators remains a significant yet challenging issue in intelligent vehicles.This paper presents a robust optimal path tracking control for intelligent vehicles equipped with a novel wheel module.A wheel module,named corner drive system(CDS),is proposed by integrating drive,brake,steering,and suspension subsystems.In light of the multi-actuator-integrate characteristic of the CDS,a reconfigurable concept is adopted to carry out the vehicle dynamics modeling.To realize an invariance system for both parametric and nonparametric uncertainties,an integral sliding mode control(ISMC)scheme is devised for desired path tracking by combining the advantages of linear quadratic regulator(LQR)in optimization and SMC in robustness.The chattering problem of the ISMC is analyzed and two continuous controllers for chattering elimination are proposed.A control allocation strategy is proposed to dynamically assign the virtual inputs generated by ISMC among four wheels to optimize vehicle stability and minimize energy dissipation.The superiority of the proposed control scheme is demonstrated under different chassis layouts,road friction conditions,and benchmark controllers on a CarSim-based high-fidelity vehicle model with simulation comparison.Subsequently,the Hardware-in-the-Loop(HiL)test is carried out to further evaluate the feasibility and real-time control performance.The quantitative results demonstrate the path tracking performance of the proposed robust optimal controller under both parametric and nonparametric uncertainties.
基金Project(2009AA045004)supported by the Hi-tech Research and Development Program of China
文摘A fuzzy robust path tracking strategy of an active pelagic trawl system with ship and winch regulation is proposed.First,nonlinear mathematic model of the pelagic trawl system was derived using Lagrange equation and further simplified as a low order model for the convenience of controller design.Then,an active path tracking strategy of pelagic trawl system was investigated to improve the catching efficiency of the target fish near the sea bottom.By means of the active tracking control,the pelagic trawl net can be positioned dynamically to follow a specified trajectory via the coordinated winch and ship regulation.In addition,considering the system nonlinearities,modeling uncertainties and the unknown exogenous disturbance of the trawl system model,a nonlinear robust H2 /H∞ controller based on Takagi-Sugeno(T-S) fuzzy model was presented,and the simulation comparison with linear robust H2 /H∞ controller and PID method was conducted for the validation of the nonlinear fuzzy robust controller.The nonlinear simulation results show that the average tracking error is 0.4 m for the fuzzy robust H2 /H∞ control and 125.8 m for the vertical and horizontal displacement,respectively,which is much smaller than linear H2 /H∞ controller and the PID controller.The investigation results illustrate that the fuzzy robust controller is effective for the active path tracking control of the pelagic trawl system.
