文献类型：期刊文献

英文题名：Adaptive neural network output feedback control for a class of non-affine non-linear systems with unmodelled dynamics

作者：Du, H.[1];Ge, S. S.[2];Liu, J. K.[3]

机构：[1]E China Univ Sci & Technol, Dept Automat, Shanghai 200237, Peoples R China;[2]Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 117576, Singapore;[3]Beijing Univ Aeronaut & Astronaut, Dept Intelligent Syst & Control Engn, Sch Automat Sci & Elect Engn, Beijing 100083, Peoples R China

年份：2011

卷号：5

期号：3

起止页码：465

外文期刊名：IET CONTROL THEORY AND APPLICATIONS

收录：;EI(收录号：20120914823753);WOS:【SCI-EXPANDED(收录号:WOS:000289461100005)】；

基金：The authors are grateful to the many constructive comments from the anonymous Associate Editor and reviewers. This work was supported by the National Nature Science Foundation of China under Grant 60704013. The authors would like to thank Professor H. K. Khalil for the helpful enlightenment about the separation principle designs. The authors are thankful to Dr. Pey Yuen Tao and Dr. Mou Chen for their helps.

语种：英文

外文关键词：Adaptive control systems - Closed loop control systems - Embedded systems - Functions - Feedback - Linear systems

摘要：In this study, an output feedback-based adaptive neural controller is presented for a class of uncertain non-affine pure-feedback non-linear systems with unmodelled dynamics. Two major technical difficulties for this class of systems lie in: (i) the few choices of mathematical tools in handling the non-affine appearance of control in the systems, and (ii) the unknown control direction embedded in the unknown control gain functions, in great contrast to the standard assumptions of constants or bounded time-varying coefficients. By exploring the new properties of Nussbaum gain functions, stable adaptive neural network control is possible for this class of systems by using a strictly positive-realness-based filter design. The closed-loop system is proven to be semi-globally uniformly ultimately bounded, and the regulation error converges to a small neighbourhood of the origin. The effectiveness of the proposed design is verified by simulations.