Monotonic Newton method based ILC with parameter optimization for non-linear systems

摘要

Despite the significant progress on iterative learning control (ILC) in the past decade, ILC algorithms for non-linear systems are still under development. Monotonic convergence is one of the desirable properties of non-linear ILC. In this paper, by introducing a relaxation index, a Newton method based ILC is shown to converge monotonically. Simulations verify the effectiveness of the new algorithm. Potential improvements are discussed for future work.