含有时变延迟的双线性参数化系统的重复学习控制

针对一类含有时变延迟的双线性参数化时变系统,提出了一种新的重复学习控制方案.该方案假设未知时变参数、未知时滞和参考信号的共同周期是已知的,通过重构系统方程,有效地消除时变延迟的影响,采用微分—差分耦合参数周期自适应律估计时变和时不变参数,可以处理参数在一个未知紧集内周期性快时变的非线性系统,通过构造一个Lyapunov-Krasovskii能量函数,证明所有信号有界并且跟踪误差渐近收敛.给出了闭环系统收敛的一个充分条件.仿真结果验证了控制算法的有效性.

Repetitive Learning Control for Bilinear Parametric Systems with Unknown Time-varying Delays

A repetitive learning control strategy is developed for a class of bilinear parametric time-varying systems with mixed unknown time-varying and time-invariant parameters and unknown time varying delay.The proposed control law includes a differential-difference coupled-type adaptive law used to estimate the unknown time-varying parameters and an adaptive repetitive learning control.By constructing a Lyapunov-Krasovskii energy function,we prove the stability of the closed loop system and the asymptotic convergence of the tracking error.The simulation results confirm the effectiveness of the proposed control scheme.