Optimal algorithm and application for point to point iterative learning control via updating reference trajectory
TAO Hong-feng
DONG Xiao-qi
YANG Hui-zhong
Abstract：For the output tracking control problem of discrete linear system with non-repetitive disturbance, a point to point iterative learning control algorithm based on updating reference trajectory is proposed. Firstly, the iterative learning controller is optimized by constructing performance index with norm function, and the corresponding convergence con-ditions are given, then the system output can track with the desired points in updating reference trajectory. Furthermore, when the system output is affected by non-repetitive disturbance in some trials, a new multi-objective performance index function is constructed by Lagrange multiplier algorithm, and the robust iterative learning controller is optimized to im-prove the convergence speed and tracking accuracy. Finally, the simulation results of the motor driven single mechanical arm control system show the effectiveness and feasibility of the proposed algorithm.
Keywords：updating reference trajectoryiterative learning controlperformance indexLagrange multiplierpoint to point
Publication Date：2016-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 1207-1213 )