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

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3 Author(s)
Petre, E. ; Dept. of Autom. Control, Univ. of Craiova, Craiova ; Selisteanu, D. ; S̀§endrescu, D.

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.

Published in:

Control, Automation and Systems, 2008. ICCAS 2008. International Conference on

Date of Conference:

14-17 Oct. 2008

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