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
Proceedings Article
Run-to-Run Iterative Optimization Control of Batch Processes.
TL;DR: In this article, a recurrent neural network (RNN) is used to model product quality of batch processes from process operational data, and the modified model errors are reduced from run to run.
Proceedings ArticleDOI
An integro-differential approach to control-oriented modelling and multivariable norm-optimal iterative learning control for a heated rod
Harald Aschemann,Andreas Rauh +1 more
TL;DR: Aiming at an accurate tracking of repetitive desired trajectories, a multivariable temperature control is proposed for a metallic rod using norm-optimal iterative learning control techniques.
Journal ArticleDOI
A convex optimization design of robust iterative learning control for linear systems with iteration‐varying parametric uncertainties
TL;DR: In this article, a robust iterative learning control (ILC) algorithm was proposed for linear systems in the presence of iteration-varying parametric uncertainties, where the robust ILC design was formulated as a min-max problem using a quadratic performance criterion subject to constraints of the control input update.
Proceedings ArticleDOI
An application of spatial Iterative Learning Control to micro-additive manufacturing
TL;DR: This manuscript demonstrates that SILC applied to this combined manufacturing and in situ metrology system is capable, through successive iterations, of automatically creating a material droplet array that approximates an ideal material topography by compensating for process variability.
Journal ArticleDOI
Ellipsoid invariant set-based robust model predictive control for repetitive processes with constraints
Jingyi Lu,Zhixing Cao,Furong Gao +2 more
TL;DR: In this paper, a robust model predictive controller, with an iterative learning control incorporated under the 2D framework, is designed for constrained repetitive processes, which can explicitly guarantee 2D stability and consistent feasibility, making all choices of tuning parameters feasible to constraints.
References
More filters
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.
Book
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.