A neural predictive controller for non-linear systems

Mircea Lazar and Octavian Pastravanu

Mathematics and Computers in Simulation (MATCOM), 2002, vol. 60, issue 3, 315-324

Abstract: Design and implementation are studied for a neural network-based predictive controller meant to govern the dynamics of non-linear processes. The advantages of using neural networks for modeling non-linear processes are shown together with the construction of neural predictors. The resulting implementation of the neural predictive controller is able to eliminate the most significant obstacles encountered in non-linear predictive control applications by facilitating the development of non-linear models and providing a rapid, reliable solution to the control algorithm. Controller design and implementation are illustrated for a plant frequently referred to in the literature. Results are given for simulation experiments, which demonstrate the effectiveness of the proposed approach.

Keywords: Control architectures; Predictive control; Neural control; Non-linear system identification; Neural network models; Neural predictors (search for similar items in EconPapers)
Date: 2002
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:60:y:2002:i:3:p:315-324

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