本文针对多频窄带未知和时变扰动,基于内模原理和Y-K参数化方法,提出一种反馈鲁棒自适应振动的主动控制算法。该算法通过设计PID中央鲁棒控制器,有效解决了次级通道模型未知情况下的鲁棒控制器参数设计问题。同时提出一种变步长最小均方...本文针对多频窄带未知和时变扰动,基于内模原理和Y-K参数化方法,提出一种反馈鲁棒自适应振动的主动控制算法。该算法通过设计PID中央鲁棒控制器,有效解决了次级通道模型未知情况下的鲁棒控制器参数设计问题。同时提出一种变步长最小均方(Variable Step Size Least Mean Square,VSSLMS)方法,可以在保证稳态误差的基础上大幅提升收敛速度,并通过系统辨识实验验证了所提VSSLMS方法相较于其他VSSLMS算法在收敛性能上的优越性。通过结构微振动主动控制实时实验,对比验证了单独采用滤波x最小均方(Least Mean Square,LMS)自适应控制算法、基于LMS算法的鲁棒自适应控制算法和基于VSSLMS算法的鲁棒自适应控制算法的抑振效果。实验结果表明,本文基于VSSLMS算法的鲁棒自适应控制算法在面向双频正弦窄带扰动以及其频谱、幅值突变情况时,都具有较好的收敛性和鲁棒性。展开更多
This paper presents a hybrid control approach,termed Model Predictive Backstepping Control,for steering angle manipulation.The design of stepping manifolds in the backstepping control incorporates the Lyapunov functio...This paper presents a hybrid control approach,termed Model Predictive Backstepping Control,for steering angle manipulation.The design of stepping manifolds in the backstepping control incorporates the Lyapunov function,posing a challenge in determining optimal stepping parameters for each manifold.In contrast to the predominant focus on constant stepping coefficients in existing research,this study explores the less investigated variable approach.Stepping parameters are introduced as tunable variables and incorporated into a backstepping control law,computed using model predictive control with the backstepping control law using tunable variables as the system input.The hybrid control algorithm utilizes prior knowledge of the control system to identify optimal values for the stepping parameters.The paper comprehensively explores model predictive backstepping control applied to a steer-by-wire system,specifically addressing the resolution of variable stepping parameters through a cost function.The developed algorithm is implemented into a steering control unit and subsequently validated in a real-world steering test vehicle.The results demonstrate successful realization of angle following in the steerby-wire system within an engineering practice context.展开更多
文摘本文针对多频窄带未知和时变扰动,基于内模原理和Y-K参数化方法,提出一种反馈鲁棒自适应振动的主动控制算法。该算法通过设计PID中央鲁棒控制器,有效解决了次级通道模型未知情况下的鲁棒控制器参数设计问题。同时提出一种变步长最小均方(Variable Step Size Least Mean Square,VSSLMS)方法,可以在保证稳态误差的基础上大幅提升收敛速度,并通过系统辨识实验验证了所提VSSLMS方法相较于其他VSSLMS算法在收敛性能上的优越性。通过结构微振动主动控制实时实验,对比验证了单独采用滤波x最小均方(Least Mean Square,LMS)自适应控制算法、基于LMS算法的鲁棒自适应控制算法和基于VSSLMS算法的鲁棒自适应控制算法的抑振效果。实验结果表明,本文基于VSSLMS算法的鲁棒自适应控制算法在面向双频正弦窄带扰动以及其频谱、幅值突变情况时,都具有较好的收敛性和鲁棒性。
基金supported by Key Research and Development Program of Jiangsu Province under granted BE2021006-2Natural Science Foundation of Anhui Province under granted 2308085ME163Foundation of State Key Laboratory of Automotive Simulation and Control.
文摘This paper presents a hybrid control approach,termed Model Predictive Backstepping Control,for steering angle manipulation.The design of stepping manifolds in the backstepping control incorporates the Lyapunov function,posing a challenge in determining optimal stepping parameters for each manifold.In contrast to the predominant focus on constant stepping coefficients in existing research,this study explores the less investigated variable approach.Stepping parameters are introduced as tunable variables and incorporated into a backstepping control law,computed using model predictive control with the backstepping control law using tunable variables as the system input.The hybrid control algorithm utilizes prior knowledge of the control system to identify optimal values for the stepping parameters.The paper comprehensively explores model predictive backstepping control applied to a steer-by-wire system,specifically addressing the resolution of variable stepping parameters through a cost function.The developed algorithm is implemented into a steering control unit and subsequently validated in a real-world steering test vehicle.The results demonstrate successful realization of angle following in the steerby-wire system within an engineering practice context.
