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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TL;DR: VLSI offers the speed and density required to implement a system implementing an unsupervised learning rule that generates linearly separable representations that capture important statistical information from the inputs.
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Event-Triggered Multiple-Model Identifier for a Class of Nonlinear Systems
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Neural Network Modelling and Control of a Plant Exhibiting the Jump Phenomena
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Dynamic Systems Numerical Integrators in Neural Control Schemes
TL;DR: A mixed heuristic and theoretical approach is taken to propose and show how to use dynamic systems ordinary differential equations (ODE) numerical integrators in control schemes where a discrete forward internal model is needed.
Book ChapterDOI
Induction of control rules from human skill
Kenneth J. Hunt,Y.M. Han +1 more
TL;DR: The aim of this endeavour is to install the induced rules from past records of skilled human behaviour as an automatic control program; it is anticipated that this will lead to more consistent and reliable control performance.
References
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Journal ArticleDOI
Approximation by superpositions of a sigmoidal function
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.
Book
Feedback Systems: Input-output Properties
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.
Book
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.