Parallel distributed neuro-fuzzy model predictive controller applied to a hydro turbine generator

Model predictive control (MPC) has been considered as the most important development in the area of process control in the last two decades. This paper addresses the issue of controlling a nonlinear plant by the use of the nonlinear model predictive control formulation. To handle the nonlinearities, a Takagi-Sugeno neuro-fuzzy model is suggested as a means to model the plant with nonlinearities depending on the operating region. The developed model is used as a predictive model for a parallel distributed model predictive control algorithm. In this paper, the parallel distributed neuro-fuzzy model predictive controller has been proposed to control a non-linear control system of a hydro turbine generator. The proposed technique has been tested and evaluated using this simulated industrial plant.