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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A neural Linearizing Control Scheme for Nonlinear Chemical Processes
Suk-joon Kim,Sunwon Park +1 more
Journal ArticleDOI
An Adaptive Neuro-Fuzzy Approach to Control a Distillation Column
TL;DR: A control strategy that enhances a fuzzy controller with self-learning capability for achieving the control of a binary methanol-propanol distillation column using an Adaptive-Network-based Fuzzy Inference System extended to cope with multivarible systems is used.
Proceedings Article
Comparison between different Control Strategies using Neural Networks
Dias F. Morgado,Alexandre Mota +1 more
Journal ArticleDOI
Multi-loop Internal Model Controller Design Based on a Dynamic PLS Framework
Bin Hu,Pingyou Zheng,Jun Liang +2 more
TL;DR: In this article, a multi-loop internal model control (IMC) scheme in conjunction with feed-forward strategy based on the dynamic partial least squares (DyPLS) framework is proposed.
Journal ArticleDOI
Tracking control of electro-hydraulic servo multi-closed-chain mechanisms with the use of an approximate nonlinear internal model
TL;DR: In this paper, the trajectory tracking problem of a hydraulic servo multi-closed-chain mechanism was studied and a nonlinear control algorithm was proposed, that is, the approximate internal model control (AIMC) integrated with a position feedback control in cascade control design.
References
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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.