一类严格反馈非线性系统的自适应神经网络控制  

Adaptive Neural Network Control for a Class of Strict-Feedback Nonlinear Systems

作　　者：丁红[1] 李红春[1] 

机构地区：[1]江海职业技术学院,江苏扬州225101

出　　处：《扬州职业大学学报》2014年第1期43-48,共6页Journal of Yangzhou Polytechnic College

基　　金：江苏省高校"青蓝工程"资助项目(苏教师[2012]39号)

摘　　要：对一类具有摄动的严格反馈非线性系统,基于动态面控制技术,提出一种自适应神经网络的控制器的设计方案。该方法消除了严格反馈非线性系统后推设计中,由于反复求导而导致的复杂性问题。通过对下界的讨论,避免间接控制中的奇异性问题。利用李亚普诺夫方法,证明闭环系统是半全局一致终结有界,且通过适当选择参数,跟踪误差收敛可以达到任意小。仿真结果表明所提控制方法的有效性。In this paper,a novel design scheme of adaptive neural network controller is proposed for a class of strict-feedback nonlinear system with perturbation based on dynamic surface control technique. The problem of explosion of complexity in traditional back stepping design is eliminated by utilizing dynamic surface control. By discussing the low bound,the singularity of adaptive controller is avoided in indirect control. Using Lyapunov method,the closed-loop systems is proved to be semi-globally uniformly ultimately bounded,with arbitrary small tracking error by appropriately choosing design constants. The simulation result indicates the effectiveness of the proposed controlling method.

关 键 词：自适应控制 神经网络 严格反馈系统 动态面控制 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]