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
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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
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Journal ArticleDOI
Quasi-Newton-type optimized iterative learning control for discrete linear time invariant systems
Yan Geng,Xiaoe Ruan +1 more
TL;DR: In this article, a quasi-Newton-type optimized iterative learning control (ILC) algorithm is investigated for a class of discrete linear time-invariant systems, which is to update the learning gain matrix by a quasi Newton-type matrix instead of the inversion of the plant.
Proceedings ArticleDOI
Low-order system identification and optimal control of intersample behavior in ILC
TL;DR: A multirate, parametric, and low-order approach to both identification for ILC and subsequent optimal ILC is presented that results in a low computational burden and appropriately deals with the time-varying nature of multirates systems.
Journal ArticleDOI
Norm-Optimal Iterative Learning Control for a High-Speed Linear Axis with Pneumatic Muscles
TL;DR: In this article, a nonlinear mechanism consisting of a rocker with a pair of pneumatic muscle actuators arranged at both sides is used to drive a new linear axis.
Proceedings ArticleDOI
Comparing the performance of two iterative Learning Controllers with optimal feedback control
TL;DR: The tracking performance of two iterative learning control algorithms is compared to that, which can be achieved by an optimal feedback controller, and the norm-optimal ILC improves upon this performance by reducing the mse by an extra order of magnitude.
Improving perfomance in single-link flexible manipulator using hybrid learning control
TL;DR: In this paper, an iterative learning control method for a single-link flexible manipulator is proposed to achieve precise tracking control and end-point vibration suppression of the system, which is done in a feedback configuration with hybrid control.
References
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Numerical recipes in C
TL;DR: The Diskette v 2.06, 3.5''[1.44M] for IBM PC, PS/2 and compatibles [DOS] Reference Record created on 2004-09-07, modified on 2016-08-08.
Book
Optimization by Vector Space Methods
TL;DR: This book shows engineers how to use optimization theory to solve complex problems with a minimum of mathematics and unifies the large field of optimization with a few geometric principles.
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Optimal Control
TL;DR: Reading optimal control frank l lewis solution manual ebook pdf 2019 is extremely useful because you could get enough detailed information in the book technology has.