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浙江大学学报(工学版)
J4  2012, Vol. 46 Issue (5): 853-857    DOI: 10.3785/j.issn.1008-973X.2012.05.013
自动化技术、电气工程     
控制方向未知的非线性系统的自适应评价设计
崔黎黎, 张化光,罗艳红
东北大学 信息科学与工程学院,辽宁 沈阳 110819
Adaptive critic design of nonlinear system with unknown control direction
CUI Li-li, ZHANG Hua-guang, LUO Yan-hong
School of Information Science and Engineering, Northeastern University, Shenyang 110819, China
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摘要：

针对一类具有未知控制方向的非仿射非线性系统,提出一种新型的基于模糊小波神经网络的鲁棒自适应评价设计.利用中值定理和Nussbaum函数处理非线性函数隐含控制输入及控制方向未知问题.采用2个具有相同模糊基函数的模糊小波神经网络(fuzzy wavelet networks, FWNs)分别实现控制单元和评价单元,FWNs的权值、扩张参数及平移参数均在线调节.为了抑制FWNs近似误差,利用自适应界化技术设计一个鲁棒项.该设计不需要控制方向及不确定项上界的先验知识.通过 Lyapunov 理论严格证明闭环系统的半全局一致最终有界稳定性.仿真结果验证所提出设计的有效性.
Abstract:

A novel fuzzy wavelet network based robust adaptive critic design was proposed for a class of non-affine nonlinear system with unknown control direction. The mean value theorem and Nussbaum function were used to handle with the problem of the nonlinear functions being implicitly functions with respect to the control input and the control direction being unknown. Two fuzzy wavelet networks (FWNs) with the same fuzzy basis functions were employed to implement the control element and the critic element, the weights, dilation and translation parameters of which were tuned online. In order to attenuate FWNs approximation errors, a robust term was designed by adaptive bounding technique. No a prior knowledge of the control direction and bound of uncertainty is needed. Moreover, the semi-globally uniformly ultimate boundedness of the closed-loop system was proved by Lyapunov theory. Simulation results demonstrate the effectiveness of the proposed design．
出版日期: 2012-05-01
:  TP 13  
基金资助:

国家自然科学基金资助项目(50977008,61034005) .
通讯作者: 张化光,男,教授，博导.     E-mail: zhanghuaguang@mail.neu.edu.cn
作者简介: 崔黎黎（1983-）,女,博士生,从事非线性系统、近似动态规划等方向研究. E-mail:cuilili8396@163.com
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引用本文:

崔黎黎, 张化光,罗艳红. 控制方向未知的非线性系统的自适应评价设计[J]. J4, 2012, 46(5): 853-857.

CUI Li-li, ZHANG Hua-guang, LUO Yan-hong. Adaptive critic design of nonlinear system with unknown control direction. J4, 2012, 46(5): 853-857.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2012.05.013    或    http://www.zjujournals.com/eng/CN/Y2012/V46/I5/853

［1］ PROKHOROV D V, WUNSCH D C. Adaptive critic designs ［J］. IEEE Translations on Neural Networks,1997,8(5)：997-1007．
［2］ SI J,BARTO A G,POWELL W B,et al. Handbook of learning and approximate dynamic programming ［M］. New York: John Wiley & Sons, 2004,15-20．
［3］ KULJACA O, LEWIS F L. Adaptive critic design using nonlinear network structure ［J］. International Journal of Adaptive Control and Signal Progress,2003,17(6)：431-445．
［4］ KIM Y H, LEWIS F L. Reinforcement adaptive learning neuralnetbased friction compensation control for high speed and precision ［J］. IEEE Translations on Control System Technology, 2000, 8(1)：118-126．
［5］ WEI Qinglai,ZHANG Huaguang,CUI Lili. Databased optimal control for discretetime zerosum games of 2D systems using adaptive critic designs ［J］. ACTA Automatica Sinica,2009,35(6)：682-692．
［6］ ZHANG Huaguang,LUO Yanhong,LIU Derong. RBF neural networkbased nearoptimal control for a class of discretetime affine nonlinear systems with control constraints ［J］. IEEE Translations on Neural Networks,2009,20(9)：1490-1503．
［7］ YANG Q,VANCE J B, JAGANNATHAN S. Control of nonaffine nonlinear discretetime systems using reinforcementlearningbased linearly parameterized neural networks ［J］. IEEE Translations on Systems, Man, and Cybernetics, Part B: Cybernetics,2008,38(4)：994-1001．
［8］ ZHANG T,GE S S. Adaptive neural network tracking control of MIMO nonlinear systems with unknown deadzones and control directions ［J］. IEEE Translations on Neural Networks,2009,20(3)：483-497．
［9］ GE S S,ZHANG T. Neuralnetwork control of nonaffine nonlinear system with zero dynamics by state and output feedback ［J］. IEEE Translations on Neural Networks,2003,14(4)：900-918．
［10］ LIN C K.H∞Reinforcement learning control of robot manipulators using fuzzy wavelet networks ［J］. Fuzzy sets and Systems,2009,160(12)：1765-1786．
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