Modular Design of Adaptive Robust Controller for a Class of Stochastic Nonlinear Systems
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- 英文论文题名：Modular Design of Adaptive Robust Controller for a Class of Stochastic Nonlinear Systems
- 论文作者：Jun Wang ; Xiao-Dong Du ; Min-Liang Feng
- 英文论文作者：Jun Wang ; Xiao-Dong Du ; Min-Liang Feng ; Department of Mechanical Engineering ; Hefei University
- 年：2017
- 作者机构：Department of Mechanical Engineering,Hefei University;
- 英文论文关键词：Stabilization in probability ; disturbance-to-state stability ; Swapping technique ; gradient update laws
- 会议召开时间：2017-07-26
- 会议录名称：第36届中国控制会议论文集（B）
- 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
- 语种：英文
- 分类号：TP273
- 学会代码：KZLL
- 会议名称：第36届中国控制会议
- 会议地点：中国辽宁大连
- 主办单位：中国自动化学会控制理论专业委员会
- 学会名称：中国自动化学会控制理论专业委员会
- 页数：4
- 文件大小：390k
- 原文格式：D
- 会议级别：全国
摘要
A modular approach of the estimation-based design in the adaptive linear control systems has been extended to the adaptive robust control of strict-feedback stochastic nonlinear systems with additive standard Wiener noises and constant unknown parameters. Using Ito?c differentiation rule, nonlinear damping and adaptive Backstepping procedure, the disturbance-to-state stable controller of global stabilization in probability is developed which guarantees system states are bounded and has a robust stabilization. According to Swapping technique, we develop two filters and convert dynamic parametric models into static ones to which the gradient update law is designed. Transient performance of the system is estimated by bounds for the error. Results of simulation show the effectiveness of the control algorithms. The hierarchy of modular design technique is concise, and the modular design is more flexible and versatile than a Lyapunov-based algorithm.
A modular approach of the estimation-based design in the adaptive linear control systems has been extended to the adaptive robust control of strict-feedback stochastic nonlinear systems with additive standard Wiener noises and constant unknown parameters. Using Ito?c differentiation rule, nonlinear damping and adaptive Backstepping procedure, the disturbance-to-state stable controller of global stabilization in probability is developed which guarantees system states are bounded and has a robust stabilization. According to Swapping technique, we develop two filters and convert dynamic parametric models into static ones to which the gradient update law is designed. Transient performance of the system is estimated by bounds for the error. Results of simulation show the effectiveness of the control algorithms. The hierarchy of modular design technique is concise, and the modular design is more flexible and versatile than a Lyapunov-based algorithm.
A modular approach of the estimation-based design in the adaptive linear control systems has been extended to the adaptive robust control of strict-feedback stochastic nonlinear systems with additive standard Wiener noises and constant unknown parameters. Using Ito?c differentiation rule, nonlinear damping and adaptive Backstepping procedure, the disturbance-to-state stable controller of global stabilization in probability is developed which guarantees system states are bounded and has a robust stabilization. According to Swapping technique, we develop two filters and convert dynamic parametric models into static ones to which the gradient update law is designed. Transient performance of the system is estimated by bounds for the error. Results of simulation show the effectiveness of the control algorithms. The hierarchy of modular design technique is concise, and the modular design is more flexible and versatile than a Lyapunov-based algorithm.
引文
[1]A.Moosavian,F.Xi,Modular design of parallel robots with static redundancy,Mechanism and Machine Theory,96(1):26–37,2016.
[2]J.Wang,M.Zhang and H.S.Xi,Modular design of robust adaptive controller for strict-feedback stochastic nonlinear systems,Control and Decision(in Chinese),20(3):1269–1273,2005.
[3]J.Wang,H.S.Xi and H.B.Ji,Robust adaptive control for a class of stochastic nonlinear systems based on gradient algorithms,Journal of University of Science and Technology of China(in Chinese),34(2):495-503,2004.
[4]K.Salonitis,Modular design for increasing assembly automation CIRP Annals-Manufacturing Technology.2014:189–192.
[5]M.Krstic and H.Deng,Stabilization of Nonlinear Uncertain Systems,London:Springer Verlag,1998.
[2]J.Wang,M.Zhang and H.S.Xi,Modular design of robust adaptive controller for strict-feedback stochastic nonlinear systems,Control and Decision(in Chinese),20(3):1269–1273,2005.
[3]J.Wang,H.S.Xi and H.B.Ji,Robust adaptive control for a class of stochastic nonlinear systems based on gradient algorithms,Journal of University of Science and Technology of China(in Chinese),34(2):495-503,2004.
[4]K.Salonitis,Modular design for increasing assembly automation CIRP Annals-Manufacturing Technology.2014:189–192.
[5]M.Krstic and H.Deng,Stabilization of Nonlinear Uncertain Systems,London:Springer Verlag,1998.