非线性系统在初态误差下的2D迭代学习算法

2D Iterative Learning Algorithm of Nonlinear System with Initial State Error

针对一类具有重复运动特性的非线性离散系统,提出了一种开闭环迭代学习控制算法,基于2D Roesser理论,得到存在初态误差情况下的收敛条件,证明算法能够收敛到一个关于初态误差的邻域内,提高了系统的响应速率,理论分析与仿真验证了算法的有效性。

For a class of nonlinear discrete-time systems with repeated movement characteristics, this paper proposes a open-closed loop of iterative learning control algorithm, based on 2D Roesser theory,analyzes the convergence condition of the presence of initial state error, and proves that the algorithm can converge to a neighborhood on initial state error, improve the response rate of the system, and the theoretical analysis and simulation prove the validity of the algorithm.