具有输入死区的非线性纯反馈系统的Backstepping控制设计  

Backstepping Control Design of Nonlinear Pure Feedback System with Input Dead Zone

作　　者：孙莉莉 陈兵[1] 王芳 SUN Lili;CHEN Bing;WANG Fang(Institute of Complexity Science,Qingdao University,Qingdao 26G071,China)

机构地区：[1]青岛大学复杂性科学研究所,山东青岛266071

出　　处：《青岛大学学报（工程技术版）》2018年第3期15-21,共7页Journal of Qingdao University(Engineering & Technology Edition)

基　　金：国家自然科学基金资助项目(61473160)

摘　　要：针对一类具有未知死区的非线性纯反馈系统自适应神经网络控制问题,本文提出了基于径向基函数神经网络结构特征的控制设计方案。将未知输入死区表示成一个线性死区与一个有界非线性死区之和的形式,在控制设计过程中,通过神经网络系统逼近未知非线性函数,结合自适应Backsteeping方法及神经网络基函数向量的范数性质,设计了一种自适应神经网络状态控制器,并通过Lyapunov稳定性理论进行稳定性分析。分析结果表明,在该控制方案作用下,闭环系统的所有信号有界,跟踪误差收敛到原点一个足够小的领域,数值仿真验证了本文方法的有效性。该研究具有一定的实用价值。This paper studies the adaptive neural network control for a class of nonlinear pure feedback systems with unknown dead zone. A neural network control design scheme is proposed based on the structural feature of the basis vector function of neural network. In the process of control design, the neural networks are applied to approximate the unknown nonlinear functions, and the adaptive technique and Backstepping method are corn bined to construct the ideal controller for the dynamic system. For the unknown input dead zone, it is ex pressed as the sum of two parts, one part is the sum of the dead zone input and dead zone parameters which are linear, and the another part is the sum of bounded nonlinear perturbation. By using Lyapunov theory, it is veri lied that under the action of the proposed controller all the signal of the closed loop are bounded, and the track ing error converges to a small area of the origin. Numerical simulations verify the effectiveness of the proposed method.

关 键 词：纯反馈非线性系统 输入死区 自适应控制 BACKSTEPPING 神经网络 状态反馈 

分 类 号：TP273.2[自动化与计算机技术—检测技术与自动化装置]