关键字：Adaptive iterative learning control; non-parametric uncertainties; nonlinear discrete-time system; random initial condition; iteration-varying target trajectories

摘要：This paper presents a new discrete-time adaptive iterative learning control approach (AILC) for a class of time-varying nonlinear systems with nonparametric uncertainties and non-repeatable external disturbances by incorporating a novel iterative estimate scheme. A major distinct feature of the presented approach is that uncertainties can be completely compensated for, using only I/O data. Another distinct feature is that the pointwise convergence is achieved over a finite time interval without requiring the matching condition on initial states and reference trajectory. Rigorous mathematical analysis is developed, and simulation results illustrate the effectiveness of the proposed approach.

卷号：15

期号：2

是否译文：否