具有快变时滞的1阶非线性参数化系统自适应迭代学习控制  

Adaptive Iterative Learning Control for First-Order Nonlinearly Parameterized Systems with Fast-Time-Varying Delays

作　　者：胡云安[1] 韦建明[2] 

机构地区：[1]海军航空工程学院控制工程系,山东烟台264001 [2]海军航空工程学院研究生管理大队,山东烟台264001

出　　处：《信息与控制》2012年第6期747-751,759,共6页Information and Control

摘　　要：针对一类具有未知快变时滞的1阶非线性参数化系统,提出了一种自适应迭代学习控制方案.为克服未知快变时滞不确定项给控制器设计带来的困难,提出了一种新型的指数型Lyapunov-Krasovskii泛函.通过对系统进行参数化,设计了控制器和未知时变参数的自适应迭代学习律.通过构造一个指数型Lyapunov-Krasovskii复合能量函数,证明了所有信号的有界性和跟踪误差的收敛性.最后通过仿真算例验证了所提出算法的有效性.An adaptive iterative learning control scheme is proposed for a class of first-order nonlinearly parameterized systems with unknown fast-time-varying delays. With respect to the uncertainties of the unknown fast-time-varying delays, a novel exponential-type Lyapunov-Krasovskii function is proposed to overcome the difficulty in designing the controller. The controller and adaptive iterative learning law of unknown time-varying parameters are designed by parameterizing the system. The boundedness of all signals and the convergence of tracking errors are proved by constructing an exponential-type Lyapunov-Krasovskii-like composite energy function. The effectiveness of the proposed control algorithms is verified by a simulation example.

关 键 词：快变时滞 指数型Lyapunov-Krasovskii泛函 自适应迭代学习控制(AILC) 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]