NDLI: Neural networks based adaptive control for a class of time varying nonlinear processes

Content Provider	IEEE Xplore Digital Library
Author	Petre, E. Selisteanu, D. Sendrescu, D.
Copyright Year	2008
Description	Author affiliation: Dept. of Autom. Control, Univ. of Craiova, Craiova (Petre, E.; Selisteanu, D.; Sendrescu, D.)
Abstract	The paper presents the design and analysis of some nonlinear and neural adaptive control strategies for a class of time-varying and nonlinear processes. In fact, a direct adaptive controller based on a radial basis function neural network used as online approximator to learn the time-varying characteristics of process parameters is developed and then is compared with a classical linearizing controller. The controllers design is achieved by using an input-output feedback linearization technique. Numerical simulations, conducted in the case of a strongly nonlinear, time varying and not exactly known dynamical kinetics fermentation process, are included to illustrate the behaviour and the performance of the presented control laws.
Starting Page	1355
Ending Page	1360
File Size	402899
Page Count	6
File Format	PDF
ISBN	9788995003893
DOI	10.1109/ICCAS.2008.4694355
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-14
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	ICROS
Subject Keyword	Programmable control Time varying systems Bioprocesses Neural networks Linear feedback control systems Automatic control Nonlinear control systems Control systems Adaptive control Nonlinear systems Neurofeedback
Content Type	Text
Resource Type	Article

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