2010 | OriginalPaper | Chapter
Direct Adaptive Control of an Anaerobic Depollution Bioprocess Using Radial Basis Neural Networks
Authors : Emil Petre, Dorin Şendrescu, Dan Selişteanu
Published in: Knowledge-Based and Intelligent Information and Engineering Systems
Publisher: Springer Berlin Heidelberg
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This work deals with the design and analysis of a nonlinear and neural adaptive control strategy for an anaerobic depollution bioprocess. A direct adaptive controller based on a radial basis function neural network used as on-line approximator to learn the time-varying characteristics of process parameters is developed and then is compared with a classical linearizing controller. The controller 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 wastewater biodegradation process, are included to illustrate the behaviour and the performance of the presented controller.