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
Neural Network Inverse Model Control Strategy: Discrete-Time Stability Analysis for Relative Order Two Systems
TL;DR: In this paper, a discrete-time stability analysis of a neural network inverse model control strategy for a relative order two nonlinear system is presented by representing the closed loop system in state space format and then analyzing the time derivative of the state trajectory using Lyapunov's direct method.
Journal ArticleDOI
Adaptive IMC controller design using linear multiple models
TL;DR: An adaptive IMC controller using just-in-time learning (JITL) technique for nonlinear process control is proposed based on a set of linear models obtained on-line by the JITL, and IMC filter parameter is adjusted on- line by an updating algorithm derived based on the Lyapunov method.
Proceedings ArticleDOI
Left-inversion of nonlinear fading memory systems from data
TL;DR: A method for the left-inversion of nonlinear fading memory systems from data is proposed, based on the identification of a model of the system to invert, and the computation of theleft-inverse directly from this model.
Journal ArticleDOI
Using an adaptive fuzzy-logic system to optimize the performances and the reduction of chattering phenomenon in the control of induction motor
TL;DR: The present contribution concerns the application of neuro-fuzzy approach in order to perform the responses of the speed regulation and to reduce the chattering phenomenon introduced by sliding mode control, which is very harmful to the actuators in this case and may excite the unmodeled dynamics of the system.
Journal ArticleDOI
Neuro-Fuzzy-based Improved IMC for Speed Control of Nonlinear Heavy Duty Vehicles
Anil Kumar Yadav,Prerna Gaur +1 more
TL;DR: A neuro-fuzzy based improved internal model control (I-IMC) is proposed for speed control of uncertain nonlinear heavy duty vehicle (HDV) as the standard IMC can’t tackle the nonlinear systems effectively and degrades the performance of HDV system.
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.