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
Automatization of a penicillin production process with soft sensors and an adaptive controller based on neuro fuzzy systems
Marcos J. Araúzo-Bravo,Marcos J. Araúzo-Bravo,José M. Cano-Izquierdo,Eduardo Gómez-Sánchez,Manuel J. López-Nieto,Yannis Dimitriadis,J. Lopez-Coronado +6 more
TL;DR: These modules are evaluated by training the FasArt and FasBack neuro-fuzzy systems first on simulated data and then applying the resulting IMC controllers to a simulated plant, showing that the trend of reference is captured, thus allowing high penicillin production.
Journal ArticleDOI
Inverse fuzzy-process-model based direct adaptive control
TL;DR: The proposed direct adaptive fuzzy logic controller is shown to be capable of handling non-linear and time-varying systems dynamics, providing good overall system performance.
Journal ArticleDOI
Internal Model Control for Shape Memory Alloy Actuators using Fuzzy Based preisach Model
TL;DR: In this paper, an extrema input hystory and a fuzzy inference is utilized to replace the classical Preisach model, which allows to reduce a large amount of experimental parameters and computation time.
Journal ArticleDOI
Nonlinear one-step-ahead control using neural networks: control strategy and stability design
TL;DR: Considering the case of the nonlinear processes with time delay, the extension of the mentioned neural control scheme to d-step-ahead predictive neural control is proposed to compensate the influence of the time-delay.
Journal ArticleDOI
Neural Control of the Movements of a Wheelchair
TL;DR: A new recurrent model is used as the neural network, for which the stability conditions of the complete control system are obtained and various practical tests are carried out, which show the correct performance of the actual system implemented.
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.