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S. Arimoto, S. Kawamura and F. Miyazaki, “Bettering Operation of Dynamic Systems by Learning: A New Control Theory for Servomechanism or Mechatronic Systems,” Proceedings 23rd IEEE Conference on Decision and Control, Las Vegas, Nevada, 1984, pp. 1064-1069.

has been cited by the following article:

• TITLE: Analysis and Causal Formulation Proof of an Optimal Iterative Learning Algorithm

  AUTHORS: Vassiliki Vita

  KEYWORDS: Casual Formulation, Discrete Systems, Iterative Learning Control

  JOURNAL NAME: Intelligent Control and Automation, Vol.1 No.2, November 26, 2010

  ABSTRACT: Iterative learning control (ILC) is used to control systems that operate in a repetitive mode, improving track-ing accuracy of the control by transferring data from one repetition of a task, to the next. In this paper an op-timal iterative learning algorithm for discrete linear systems is analyzed and a solution for its attainment is proposed. Finally the mathematical proof of the algorithm’s causal formulation is also provided in its com-plete form, since its implementation requires its causal formulation.