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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Dissertation
Adaptation and Learning for Manipulators and Machining
TL;DR: In this article, three different approaches to improve the robotic machining accuracy are presented, where an external compensation mechanism is used in combination with the robot, for compensation of high-frequency Cartesian errors.
Journal ArticleDOI
A neural network strategy for end-point optimization of batch processes.
TL;DR: A new approach is presented for end-point optimization of batch processes by utilizing neural networks, which alleviates the computational problems associated with the classical Pontryagin's approach and the nonlinear programming approach.
Proceedings ArticleDOI
Adaptive internal model control for mid-ranging of closed-loop systems with internal saturation
TL;DR: In this article, the problem of performing mid-ranging control of two closed-loop controlled systems that have internal saturations is considered, where an external compensation mechanism is used to compensate for position errors.
Proceedings ArticleDOI
Neural modeling and control of a diesel engine with pollution constraints
TL;DR: A neural model of the engine is designed, including the engine speed and the exhaust gas opacity estimation (pollution criterion), and some simulation results of the proposed control scheme using the model are presented.
References
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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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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.