Comparative analysis of neural predictive controllers and its application to a laboratory tank system

In this paper, a novel control strategy based on neural networks is proposed in order to reduce the computation effort of a nonlinear predictive controller. The proposed method is favorably compared with the nonlinear predictive controller and approximated predictive controller based on neural networks. Also, the control strategies are designed and evaluated by simulation tests and in real-time for a laboratory tank system.