A PD-type iterative learning control algorithm for singular discrete systems

Senping Tian,Qian Liu,Xisheng Dai,Jianxiang Zhang

doi:10.1186/s13662-016-1047-4

Abstract

Based on a specific decomposition of discrete singular systems, in this paper, we study the problem of state tracking control by using PD-type algorithm of iterative learning control. The convergence conditions and theoretical analysis of the PD-type algorithm are presented in detail. An illustrative example supporting the theoretical results and the effectiveness of the PD-type iterative learning control algorithm for discrete singular systems is shown at the end of the paper.

Highlights

1 Introduction Iterative learning control (ILC) is an effective control scheme in handling a system that repetitively perform the same task with a view to sequentially improving the accuracy on a finite interval
The aim of ILC is to look for a proper learning control algorithm of the controlled systems so that the output state can track the given desired trajectory over a finite interval time and in the meantime the constructed learning control sequences can uniformly converge to the desired control
Since Arimito proposed the concept of iterative learning control in, the research of ILC has become a topic of focus in the field of control and fruitful research progress has been made in theory and application [ – ]

Summary

Introduction

Iterative learning control (ILC) is an effective control scheme in handling a system that repetitively perform the same task with a view to sequentially improving the accuracy on a finite interval. The existing ILC methods of singular discrete systems use either a Ptype algorithm or a D-type algorithm to track the desired output trajectory. Reference [ ] studied the state tracking problem of the singular system with time-delay and proved that the iterative learning algorithm is convergent under certain conditions.

Results

Conclusion