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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Adaptive Model-Based Control using Neural Networks
TL;DR: In this article, a method for implementing a neural network model of nonlinear process dynamics for adaptive control was proposed and evaluated using two simulated realistic processes; level control of a conical tank and multivariable control of an industrial evaporator.
Proceedings ArticleDOI
Internal model control using GA-NN for boiler drum
TL;DR: An internal model control using GA-NN for the water level system of boiler drum of the power plant is presented and simulation results testify that the model is satisfied and the control is effective.
Book ChapterDOI
Neural Network Controllers
Duc Truong Pham,Xing Liu +1 more
TL;DR: Research over the last twenty years has revealed the architecture and performance characteristics of the brain as a controller and has shown that neural network controllers have important advantages over conventional controllers.
Dissertation
Utilising local model neural network jacobian information in neurocontrol
TL;DR: This dissertation aims to demonstrate the efforts towards in-situ applicability of EMMARM, as to provide real-time information about the physical properties of E-modulus and its applications in the building and construction industry.
Book ChapterDOI
Computational Intelligence Based Regulation of the DC Bus in the On-grid Photovoltaic System
TL;DR: By combining with simple proportional control, the overshoot and undershoot of the DC bus voltage that caused by sudden connections and disconnections of the local DC loads can be damped more quickly and better than the standard optimal PI control system, so the overvoltage condition of theDC bus capacitor could be avoided.
References
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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.
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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.