无反步设计的严格反馈型非线性系统神经网络自适应跟踪控制  

Neural network adaptive tracking control for strict-feedback nonlinear systems without backstepping

作　　者：胡慧[1] 刘国荣[1] 郭鹏[1] 黄峰[1] 

机构地区：[1]湖南工程学院电气信息学院,湖南湘潭411101

出　　处：《中南大学学报（自然科学版）》2012年第10期3900-3905,共6页Journal of Central South University:Science and Technology

基　　金：国家自然科学基金资助项目(5177040);省市联合自科基金重点资助项目(09JJ8006);湖南省科技计划项目(2011FJ3126);湖南省教育厅优秀青年项目(09B022)

摘　　要：针对一类具有外部干扰、仅输出可测的SISO严格反馈型非线性系统,提出一种神经网络输出反馈跟踪控制方法。该方法将严格反馈型系统转换成标准仿射型系统,从而避免反步设计过程,且无需设计状态观测器。最终控制律和神经网络权值更新律中仅用到输出误差。基于Lyapunov方法证明了闭环系统所有信号有界,跟踪误差收敛到有界紧集内。最后,应用高机动导弹的位置跟踪控制验证了该方法的有效性。An output feedback tracking control algorithm using neural network for a class of SISO strict-feedback nonlinear systems with external disturbances was presented under the constraints that only the system output variables can be measured. The method shows that the strict-feedback systems can be transformed into the standard affine form to avoid backstepping design. No state observer was employed in the algorithm. Only the output error was used in control laws and weights update laws. Moreover, all signals in the closed-loop system were guaranteed to be ultimately bounded by Lyapunov approach and output of the system converge, to a small neighborhood of the desired trajectory. Finally the tracking control of high maneuver missile was used to demonstrate the effectiveness of the control scheme.

关 键 词：输出反馈 严格反馈非线性系统 神经网络 跟踪控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]