Robust Adaptive Iterative Learning Control for Discrete-Time Nonlinear Systems With Time-Iteration-Varying Parameters
研究了离散时间非线性系统中参数随时间迭代变化时的鲁棒自适应迭代学习控制问题，提出一种新的死区方法同时估计不变部分和漂移界，保证跟踪误差有界，仿真验证了有效性。
In this paper, the robustness problem in adaptive iterative learning control for discrete-time nonlinear systems with time-iteration-varying parameters is investigated. The time-iteration-varying parameter can be expressed as the sum of an iteration-invariant time-varying part and a bounded iteration-drift term. Then a novel dead-zone method is applied in estimations of the iteration-invariant part and the drift bound simultaneously. The boundedness of tracking error is ensured by rigorous analysis. The efficacy of the proposed method is illustrated through simulation results.