Journal ArticleDOI
Neural networks for nonlinear internal model control
Kenneth J. Hunt,D. Sbarbaro +1 more
- Vol. 138, Iss: 5, pp 431-438
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TLDR
In this paper, a novel technique, directly using artificial neural networks, is proposed for the adaptive control of nonlinear systems, where the ability of neural networks to model arbitrary nonlinear functions and their inverses is exploited.Abstract:
A novel technique, directly using artificial neural networks, is proposed for the adaptive control of nonlinear systems. The ability of neural networks to model arbitrary nonlinear functions and their inverses is exploited. The use of nonlinear function inverses raises questions of the existence of the inverse operators. These are investigated and results are given characterising the invertibility of a class of nonlinear dynamical systems. The control structure used is internal model control. It is used to directly incorporate networks modelling the plant and its inverse within the control strategy. The potential of the proposed method is demonstrated by an example.read more
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Dissertation
Approches neuromimétiques pour l'identification et la commande des systèmes électriques : application au filtrage actif et aux actionneurs synchrones
TL;DR: In this article, the authors propose des approches neuromimetiques d'identification and de commande avec des applications directes au Filtre Actif Parallele (FAP) and au Moteur Synchrone a Aiment Permanent (MSAP).
Journal ArticleDOI
Radial basis function networks for internal model control
Martin Pottmann,H. Peter Jörgl +1 more
TL;DR: In this article, a nonlinear internal model control (IMC) strategy is proposed that includes explicit input weighting, which yields a control law in form of an analytical expression if a control-linear RBF model is used.
Journal ArticleDOI
Application of practical fuzzy arithmetic to fuzzy internal model control
TL;DR: A new fuzzy arithmetic of interval calculus and fuzzy quantities to automatic control, based on a different representation of fuzzy numbers, whose solutions allow creating a fuzzy internal model control scheme.
Proceedings ArticleDOI
ANN based IMC scheme for CSTR
TL;DR: This paper demonstrates that neural networks can be used effectively for control of nonlinear dynamical systems and tests the internal model control (IMC) strategy based on neural networks for process systems.
Dissertation
Design, implementation and analysis of keyed hash functions based on chaotic maps and neural networks
TL;DR: In this article, the performances of deux architectures comprenant chacune deux structures of fonctions de hachage avec cle basees sur des cartes chaotiques and des reseaux neuronaux (KCNN) are analyzed.
References
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Journal ArticleDOI
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TL;DR: It is demonstrated that finite linear combinations of compositions of a fixed, univariate function and a set of affine functionals can uniformly approximate any continuous function ofn real variables with support in the unit hypercube.
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TL;DR: In this paper, the Bellman-Gronwall Lemma has been applied to the small gain theorem in the context of linear systems and convolutional neural networks, and it has been shown that it can be applied to linear systems.
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Robust process control
TL;DR: A state-of-the-art study of computerized control of chemical processes used in industry is presented in this article for chemical engineering and industrial chemistry students involved in learning the micro-macro design of chemical process systems.
Journal ArticleDOI
Internal model control. A unifying review and some new results
Carlos E. García,Manfred Morari +1 more
Journal ArticleDOI
A multilayered neural network controller
TL;DR: A modified error-back propagation algorithm, based on propagation of the output error through the plant, is introduced, for learning several learning architectures for training the neural controller to provide the appropriate inputs to the plant.