摘要
本文对于一类含不确定输入时滞和干扰的非线性系统的跟踪控制问题提出了一种自适应动态面控制方案.利用动态面控制方法避免了传统的后推设计中存在的复杂度爆炸问题.分别构造了一个滤波器和一个虚拟观测器来产生辅助信号.采用神经网络来逼近未知的连续函数.跟踪误差被证明最终收敛到一个足够小的紧集.给出了一个数字仿真示例验证了理论结果.
Adaptive dynamic surface control is developed for the tracking control problem of a class of nonlinear systems with uncertain input delay and disturbances. The explosion of complexity in traditional backstepping design is avoided by utilizing dynamic surface control. A filter and a virtual observer are constructed respectively to produce the auxiliary signal. Neural networks are employed to approximate the unknown continuous functions. It is proved that the tracking error ultimately converges to an adequately small compact set. The theoretical result is illustrated through a simulation example.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2013年第11期1437-1444,共8页
Control Theory & Applications
基金
supported by the National Natural Science Foundation of China(Nos.61273352,61174046,61175111,60904030,60874045,60874030)
the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(Nos.10KJB510027,09KJB510019)
the Postdoctoral Science Research Project of Jiangsu Province(No.1102167C)
关键词
动态面控制
输入时滞
神经网络
自适应控制
dynamic surface control
input delay
neural network
adaptive control
