Adaptive Control of MIMO Mechanical Systems with Unknown Actuator Nonlinearities Based on the Nussbaum Gain Approach

被引:22
作者
Chen, Ci [1 ]
Liu, Zhi [1 ]
Zhang, Yun [1 ]
Chen, C. L. Philip [2 ]
Xie, Shengli [1 ,3 ]
机构
[1] Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Guangdong, Peoples R China
[2] Univ Macau, Fac Sci & Technol, Macau 999078, Peoples R China
[3] Guangdong Key Lab IoT Informat Proc, Guangzhou, Guangdong, Peoples R China
基金
中国国家自然科学基金; 国家教育部博士点专项基金资助;
关键词
Actuator nonlinearities; time varying control coefficients; Nussbaum analysis; asymptotic tracking;
D O I
10.1109/JAS.2016.7373759
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper investigates MIMO mechanical systems with unknown actuator nonlinearities. A novel Nussbaum analysis tool for MIMO systems is established such that unknown time-varying control coefficients are tackled. In contrast to existing literatures on continuous-time systems, the newly-developed Nussbaum tool focuses on extending the traditional Nussbaum result from one dimensional case to the multiple one. Specifically, not only the multiple unknown input coefficients are extended to the time-varying, but also the limitation of the prior knowledge of coefficients' upper and lower bounds is removed. Furthermore, an adaptive robust controller associated with the proposed tool is presented. The asymptotic tracking of MIMO mechanical systems is guaranteed with the help of the Lyapunov Theorem. Finally, a simulation example is provided to examine the validity of the proposed scheme.
引用
收藏
页码:26 / 34
页数:9
相关论文
共 49 条
[11]  
2-N
[12]   Adaptive autopilot design of time-varying uncertain ships with completely unknown control coefficient [J].
Du, Jialu ;
Guo, Chen ;
Yu, Shuanghe ;
Zhao, Yongsheng .
IEEE JOURNAL OF OCEANIC ENGINEERING, 2007, 32 (02) :346-352
[13]   Adaptive robust nonlinear ship course control based on backstepping and nussbaum gain [J].
Du, Jialu ;
Guo, Chen ;
Yu, Shuanghe .
INTELLIGENT AUTOMATION AND SOFT COMPUTING, 2007, 13 (03) :263-272
[14]   A robust adaptive neural networks controller for maritime dynamic positioning system [J].
Du, Jialu ;
Yang, Yang ;
Wang, Dianhui ;
Guo, Chen .
NEUROCOMPUTING, 2013, 110 :128-136
[15]   Adaptive neural control of nonlinear time-delay systems with unknown virtual control coefficients [J].
Ge, SZS ;
Hong, F ;
Lee, TH .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2004, 34 (01) :499-516
[16]   Neural network-based adaptive attitude tracking control for flexible spacecraft with unknown high-frequency gain [J].
Hu, Qinglei .
INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, 2010, 24 (06) :477-489
[17]   Adaptive iterative learning control for a class of nonlinear time-varying systems with unknown delays and input dead-zone [J].
Wei, Jianming (wjm604@163.com), 1600, Institute of Electrical and Electronics Engineers Inc. (01) :302-314
[18]  
Lewis FL., 2003, ROBOT MANIPULATOR CO
[19]   Adaptive Output Feedback NN Control of a Class of Discrete-Time MIMO Nonlinear Systems With Unknown Control Directions [J].
Li, Yanan ;
Yang, Chenguang ;
Ge, Shuzhi Sam ;
Lee, Tong Heng .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2011, 41 (02) :507-517
[20]  
Liu Y., 2014, SCI CHINA INFORM SCI, V57, P1