基于U模型的平滑自适应内模控制
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- 英文论文题名：Research on Smooth Adaptive Internal Model Control Based on U Model
- 论文作者：张玉振 ; 张维存 ; 赵栎
- 英文论文作者：Yuzhen Zhang ; Weicun Zhang ; Li Zhao ; School of Automation and Electrical Engineering ; University of Science and Technology Beijing ; Engineering Research Institute ; University of Science and Technology Beijing
- 年：2017
- 作者机构：北京科技大学自动化学院;北京科技大学冶金工程研究院;
- 论文关键词：U模型 ; 虚拟等价系统 ; 自适应
- 英文论文关键词：U Model ; Virtual Equivalent System ; Adaptive Control
- 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（A）
- 英文会议录名称：Proceedings of the 36th Chinese Control Conference（A）
- 语种：中文
- 分类号：TP273.2
- 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：6
- 文件大小：443k
- 原文格式：D
- 会议级别：全国
摘要
针对模型参数未知和存在有界干扰的不确定非线性动态系统,本文提出一种基于U模型的平滑自适应内模控制方法,实现对非线性被控对象模型的结构简化及辨识参数的精度提高。结合虚拟等价系统理论给出了系统的稳定性分析。最后,以典型非线性动态系统作为被控对象进行仿真实验验证,结果验证了本文算法的有效性和简洁性,且相较传统自适应控制器具有计算量小、控制精度高的特点,具有较高的工程实用性。
For a class of uncertain nonlinear dynamic systems with unknown model parameters and bounded external disturbance, an improved smooth adaptive internal model control method is presented to realize system structural simplification and identified parameters' improvement. Combining the virtual equivalent system theory, learning rate's stability of smooth adaptive internal model controller is analyzed and the closed-loop virtual equivalent system based on discrete U model is constructed. Finally, in the typical nonlinear dynamic system simulations, results verified the effectiveness of the proposed algorithm with simplified calculation and high control accuracy compared to the traditional adaptive controller.
For a class of uncertain nonlinear dynamic systems with unknown model parameters and bounded external disturbance, an improved smooth adaptive internal model control method is presented to realize system structural simplification and identified parameters' improvement. Combining the virtual equivalent system theory, learning rate's stability of smooth adaptive internal model controller is analyzed and the closed-loop virtual equivalent system based on discrete U model is constructed. Finally, in the typical nonlinear dynamic system simulations, results verified the effectiveness of the proposed algorithm with simplified calculation and high control accuracy compared to the traditional adaptive controller.
引文
[1]K.Hassan.Nonlinear system,third edition.Pearson Education,Inc.,2002.
[2]B.Dayal,J.Macgregor,Identification of finite impulse response models:methods and robustness issues.Ind.Eng.Chem.Res.,1996,35:4078-4090.
[3]Q.Zheng,E.Zafiriou,A local form of small gain theorem and analysis of feedback Volterra systems.IEEE Transactions on Automatic Control,1999,(03):635-640.
[4]胡德文,王正志.非线性系统wiener模型辨识.自动化学报,1991,(02):151-159.
[5]E.Bai,K.Li,Convergence of the iterative algorithm for a general Hammerstein system identification.Automatica,2010,(46):1891-1896.
[6]E.Bai,D.Li,Convergence of the iterative Hammerstein system identification algorithm.IEEE Transactions on Automatic Control,2004,(11):1929-1940.
[7]Y.Tan,L.Deng,Modeling the dynamic sandwich system with hysteresis using NARMAX model.Mathematics and Computers in Simulation,2014,97:162-188.
[8]J.Tsai,W.Hsu,L.Lin,S.Guo,J.Tann.A modified NARMAX model-based self-tuner with fault tolerance for unknown nonlinear stochastic hybrid systems with an input-output direct feed-through term.ISA Transactions,2014,53(1):56-75.
[9]Q.Zhu,L.Guo,A pole placement controller for nonlinear dynamic plant.Proc of IMechE,PartⅠ:J Systems and Control Engineering,2002,216(16):467-476.
[10]X.Wu,L.Liu,Q.Zhu,et al,U-model-based adaptive control for a class of stochastic non-linear dynamic plants with unknown parameter.Int J of Modelling,Identification and Control,2011,13(3):135-143.
[11]S.Muhammad,M.Haseebiddon,U-model-based internal model control for non-linear dynamic plants.Proc of the Institution of Mechanical Engineers,PartⅠ:J of Systems and Control Engineering,2005,219(6):449-458.
[12]S.Muhammad,K.Tahir,Newton-Raphson based adaptive inverse control scheme for tracking of nonlinear dynamic plants.The 1st Int Symposium on Systems and Control in Aerospace and Astronautics.Harbin:IEEE,2006:1339-1343.
[13]S.Ali,M.Fouad,S.Muhammad,et al.MIMO U-model based control:Real-time tracking control and feedback analysis via small gain theorem.WSEAS Trans on Circuits and Systems,2008,7(7):610-619.
[14]徐凤霞,朱全民,赵东亚,李少远.基于U模型的非线性控制系统设计方法十年发展综述.控制与决策,2013,7(28):961-971.
[15]L.Zhao,J.Wang,The application of improved parameter-adaptive algorithm based on U-model in AGC control system of cold rolling mill.IEEE ICIA,2014:311-316.
[16]W.Zhang,On the stability and convergence of self-tuning control-virtual equivalent system approach.International Journal of Control,2010,83(5):879-896.
[17]张维存.自校正控制的虚拟等价系统理论.哈尔滨工业大学学报,2014,05:107-112.
[18]吴宏鑫.自适应控制技术的应用和发展.控制理论与应用,1992,9(2):1-10.
[19]W.Zhao,H.Chen,Adaptive tracking and recursive identification for hammerstein systems.Automatica,2009,45(2):2773-2783.
[20]Y.Liu,Robust adaptive observer for nonlinear systems with unmodeled dynamics.Automatica,2009,45:1891-1895.
[2]B.Dayal,J.Macgregor,Identification of finite impulse response models:methods and robustness issues.Ind.Eng.Chem.Res.,1996,35:4078-4090.
[3]Q.Zheng,E.Zafiriou,A local form of small gain theorem and analysis of feedback Volterra systems.IEEE Transactions on Automatic Control,1999,(03):635-640.
[4]胡德文,王正志.非线性系统wiener模型辨识.自动化学报,1991,(02):151-159.
[5]E.Bai,K.Li,Convergence of the iterative algorithm for a general Hammerstein system identification.Automatica,2010,(46):1891-1896.
[6]E.Bai,D.Li,Convergence of the iterative Hammerstein system identification algorithm.IEEE Transactions on Automatic Control,2004,(11):1929-1940.
[7]Y.Tan,L.Deng,Modeling the dynamic sandwich system with hysteresis using NARMAX model.Mathematics and Computers in Simulation,2014,97:162-188.
[8]J.Tsai,W.Hsu,L.Lin,S.Guo,J.Tann.A modified NARMAX model-based self-tuner with fault tolerance for unknown nonlinear stochastic hybrid systems with an input-output direct feed-through term.ISA Transactions,2014,53(1):56-75.
[9]Q.Zhu,L.Guo,A pole placement controller for nonlinear dynamic plant.Proc of IMechE,PartⅠ:J Systems and Control Engineering,2002,216(16):467-476.
[10]X.Wu,L.Liu,Q.Zhu,et al,U-model-based adaptive control for a class of stochastic non-linear dynamic plants with unknown parameter.Int J of Modelling,Identification and Control,2011,13(3):135-143.
[11]S.Muhammad,M.Haseebiddon,U-model-based internal model control for non-linear dynamic plants.Proc of the Institution of Mechanical Engineers,PartⅠ:J of Systems and Control Engineering,2005,219(6):449-458.
[12]S.Muhammad,K.Tahir,Newton-Raphson based adaptive inverse control scheme for tracking of nonlinear dynamic plants.The 1st Int Symposium on Systems and Control in Aerospace and Astronautics.Harbin:IEEE,2006:1339-1343.
[13]S.Ali,M.Fouad,S.Muhammad,et al.MIMO U-model based control:Real-time tracking control and feedback analysis via small gain theorem.WSEAS Trans on Circuits and Systems,2008,7(7):610-619.
[14]徐凤霞,朱全民,赵东亚,李少远.基于U模型的非线性控制系统设计方法十年发展综述.控制与决策,2013,7(28):961-971.
[15]L.Zhao,J.Wang,The application of improved parameter-adaptive algorithm based on U-model in AGC control system of cold rolling mill.IEEE ICIA,2014:311-316.
[16]W.Zhang,On the stability and convergence of self-tuning control-virtual equivalent system approach.International Journal of Control,2010,83(5):879-896.
[17]张维存.自校正控制的虚拟等价系统理论.哈尔滨工业大学学报,2014,05:107-112.
[18]吴宏鑫.自适应控制技术的应用和发展.控制理论与应用,1992,9(2):1-10.
[19]W.Zhao,H.Chen,Adaptive tracking and recursive identification for hammerstein systems.Automatica,2009,45(2):2773-2783.
[20]Y.Liu,Robust adaptive observer for nonlinear systems with unmodeled dynamics.Automatica,2009,45:1891-1895.