Journal ArticleDOI
Iterative learning control for discrete-time systems with exponential rate of convergence
N. Amann,David H. Owens,Eric Rogers +2 more
- Vol. 143, Iss: 2, pp 217-224
Reads0
Chats0
TLDR
An algorithm for iterative learning control is proposed based on an optimisation principle used by other authors to derive gradient-type algorithms and has potential benefits which include realisation in terms of Riccati feedback and feedforward components.Abstract:
An algorithm for iterative learning control is proposed based on an optimisation principle used by other authors to derive gradient-type algorithms. The new algorithm is a descent algorithm and has potential benefits which include realisation in terms of Riccati feedback and feedforward components. This realisation also has the advantage of implicitly ensuring automatic step-size selection and hence guaranteeing convergence without the need for empirical choice of parameters. The algorithm achieves a geometric rate of convergence for invertible plants. One important feature of the proposed algorithm is the dependence of the speed of convergence on weight parameters appearing in the norms of the signals chosen for the optimisation problem.read more
Citations
More filters
Journal ArticleDOI
A survey of iterative learning control
TL;DR: Though beginning its third decade of active research, the field of ILC shows no sign of slowing down and includes many results and learning algorithms beyond the scope of this survey.
Linear systems
TL;DR: In this paper, the authors studied the effect of local derivatives on the detection of intensity edges in images, where the local difference of intensities is computed for each pixel in the image.
Journal ArticleDOI
Iterative Learning Control: Brief Survey and Categorization
TL;DR: The iterative learning control (ILC) literature published between 1998 and 2004 is categorized and discussed, extending the earlier reviews presented by two of the authors.
Journal ArticleDOI
Model-based iterative learning control with a quadratic criterion for time-varying linear systems
TL;DR: It is shown that, within the framework of the quadratic-criterion-based ILC (Q-ILC), various practical issues such as constraints, disturbances, measurement noises, and model errors can be considered in a rigorous and systematic manner.
Book ChapterDOI
Iterative Learning Control: An Expository Overview
TL;DR: This chapter gives an overview of the field of iterative learning control (ILC), followed by a detailed description of the ILC technique, followed by two illustrative examples that give a flavor of the nature of ILC algorithms and their performance.
References
More filters
Journal ArticleDOI
Singular optimal control problems
TL;DR: A survey of singular control problems can be found in this paper, where sufficient and sufficient conditions for nonsingular control problems have been established over the past decade, although sufficient, and necessary and sufficient, conditions have only recently been formulated.
Journal ArticleDOI
Singular optimal control: A geometric approach
TL;DR: In this article, the linear quadratic singular optimal control problem is solved for non-minimum phase and noninvertible systems, and a state space decomposition is obtained and a reduced order nonsingular subproblem is solved.
Journal ArticleDOI
Two-dimensional model and algorithm analysis for a class of iterative learning control systems
TL;DR: A class of iterative learning control systems is analysed from the point of view of two-dimensional (2-D) system theory and the 2-D model for a class of ILCS is established in the form of ‘Roessor's model’, based on which a general type of learning controller is proposed.
Journal ArticleDOI
Iterative learning control method for discrete-time dynamic systems
TL;DR: In this paper, an iterative learning control algorithm is presented for a class of linear discrete-time dynamic systems with unknown but periodic parameters, and a sufficient condition for convergency of the iterative algorithm is provided.
Journal ArticleDOI
A discrete-time design of robust iterative learning controllers
TL;DR: A simple discrete-time design of robust iterative learning controllers taking account of the transient behavior as well as the uncertainty of a plant is proposed and the controller is obtained by minimizing an averaged quadratic performance index.