一类纯反馈系统Backstepping控制设计  

Backstepping Control Design for a Class of Pure Feedback System

作　　者：孙莉莉 陈兵[1] 王芳 SUN Lili;CHEN Bing;WANG Fang(Complexity Science,Qingdao University,Qingdao 2GG071,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4期1-8,15,共9页Journal of Qingdao University(Engineering & Technology Edition)

基　　金：国家自然科学基金资助项目(61473160;61673227)

摘　　要：针对一类非线性纯反馈系统的自适应神经网络控制问题,本文提出基于径向基函数神经网络结构特征的控制设计方案。在控制设计过程中,首先设计状态观测器,估计系统中未知状态变量,通过神经网络近似未知非线性函数,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输出反馈控制方案,最后通过Lyapunov稳定性理论对系统进行分析,从而证实在所提出方案的作用下闭环系统的所有信号有界,跟踪误差收敛到原点的一个足够的小领域。数值仿真验证了本文方法的有效性。该研究解决了这类系统的状态控制问题,具有一定的实际应用价值。In this paper, adaptive neural network contro cussed. A control scheme is proposed based on structura works. In the process of control design, a state observer problem of nonlinear pure feedback systems is dis characteristics of radial basis function of neural net design scheme is first given to estimate the unknown state variables. Furthermore, a neural approximation based adaptive neural network output feedback control scheme is proposed by using backsteeping method. Finally, the Lyapunov stability theory is used to analyze the system, and all the signals of the closed loop system are bounded under the proposed scheme and the tracking error converges to a small enough area around the origin. Numerical simulation verifies the effectiveness of the proposed method.

关 键 词：纯反馈非线性系统 自适应控制 BACKSTEPPING 神经网络 输出反馈 

分 类 号：TP273.2[自动化与计算机技术—检测技术与自动化装置]