A Sliding-mode Iterative Learning Control for a Nonlinear Discrete-time System via a Data-driven Design method

Affiliation of Author(s):自动化与电子工程学院

Abstract:In this work, a sliding-mode iterative learning control(SM-ILC) is proposed for a nonlinear and non-affine discrete-time system, which is transferred into a linear incremental input-and-output form equivalently. The unknown parameters in the linear incremental input-and-output model can be estimated by using an iterative project algorithm. The optimal learning control law is developed with a sliding surface defined along the iteration direction. The proposed SM-ILC is a data-driven approach and can achieve a better control performance because much more control knowledge is utilized. Both the convergence analysis and the simulation results have been provided to show the effectiveness of the proposed method.

Translation or Not:no