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
Citations
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Journal ArticleDOI
A Study on Intelligent Control of Real-Time Working Motion Generation of Bipped Robot
TL;DR: It is shown that learning control algorithm based on the neural network is significantly more attractive intelligent controller design than previous traditional forms of control systems.
Dissertation
Composite Adaptive Internal Model Control: Theory and Applications to Engine Control
TL;DR: Motivated by the need to develop robust and easily calibratable control technologies for boost-pressure control of turbocharged gasoline engines, this thesis developed new control design methodologies in the IMC framework.
Proceedings ArticleDOI
Internal model control using modularly structured B-spline networks
TL;DR: The proposed method is based on the use of Modularity structured B spline Networks which are integrated in an Internal Model Control structure and it is shown that the networks are suitable for this control strategy due to their simple mathematical description allowing model inversion in an easy way.
Book ChapterDOI
Lime Kiln Process Identification and Control: A Neural Network Approach
TL;DR: A neural network approach for multivariable non-linear kiln process identification and control is presented and it is expected that better results can be obtained as compared to more conventional methods.
Dissertation
Arithmétique floue phi-calcul : applications à la classification et à la commande
TL;DR: In this article, the authors propose an arithmetique pratique de calcul d'intervalles and quantites floues based on logique floue.
References
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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
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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.