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
Adaptive Control Incorporating Neural Network
Adaptive Internal Model Control for Mid-Ranging of Closed-Loop Systems with Internal Saturation
TL;DR: An adaptive, modelbased solution to the problem of performing mid-ranging control of two closed-loop controlled systems that have internal saturations is presented and a performance increase of up to 56 % is obtained.
Journal ArticleDOI
Intelligent control for pneumatic servo system
TL;DR: In this article, a model reference adaptive control (MRAC) incorporating neural network (NN) for the pneumatic servo system is presented. And there is no need to use the inner parameters of the neural network during the learning of the NN.
Journal ArticleDOI
Enhancing the performance of intelligent control systems in the face of higher levels of complexity and uncertainty
TL;DR: Some approaches that appear to be promising for enhancing the performance of intelligent control systems in the face of higher levels of complexity and uncertainty are surveyed.
Journal ArticleDOI
Autotuning Method of Membership Function in a Fuzzy Learning Controller
Byeong-Mook Chung,Jun-Ho Oh +1 more
TL;DR: A learning algorithm for fuzzy inference rules that can tune both the control input and the linguistic membership function of a fuzzy controller is presented and can easily achieve good control rules with a minimal amount of prior information about the environment.
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.