Earticle

초록

영어

The repeatability of system is a fundamental requirement for various iterative learning control methods, and is a necessary condition for the outcome of perfect tracking. This paper theoretically and numerically explains that how the history before the initial time of dynamic systems influences the current state and repeatability of the system. To this end, the convergence analysis of PD-type iterative learning control for initialized system is presented. A practical preconditioning strategy is added to accelerate the convergence speed, and the detailed discussions of initialization function and initialization response are shown as well. The minimum preconditioning time interval is achieved, and some unique properties of initialized system are illustrated to provide novel challenges for robust and adaptive controls. A number of numerical simulations exhibit that a simple preconditioning process can efficiently improve the performance of the initialized iterative learning control.

목차

Abstract
 1. Introduction
 2. Preliminaries
  2.1. Laplace Transform
  2.2. Initialized System and Preconditioning
 3. The Initialized MIMO System
  3.1. Zero Initialization Function
  3.2. Finite Time Initialization Function
  3.3. Infinite Time Initialization Function
  3.4. Initialization Response
 4. Convergence Analysis
  4.1. The Case of Zero Initialization Function
  4.2. The Case of Non-Zero Initialization Function
 5. Illustrated Examples
 6. Conclusions
 References

키워드

저자

• Lun Zhai [ School of Control Science and Engineering, Shandong University, Jinan, PR China ]
• Guohui Tian [ School of Control Science and Engineering, Shandong University, Jinan, PR China ]
• Yan Li [ School of Control Science and Engineering, Shandong University, Jinan, PR China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605