Identification and control of a nonlinear bioreactor plant using classical and dynamical neural networks

Abstract

In this study, the identification and control of a bioreactor plant using neural networks is considered with three different control strategies, namely, inverse control strategy, self-learning control and dynamical neural units for control of nonlinear dynamical systems. The performance of these methods are compared using several comparison measures.