Research And Application Of Multivariable Intelligent Predictive Control

The major dynamics of the power plant include nonlinearities behavior, coupling effect, and uncertainties. Traditional control strategy could not offer satisfactory result. Using the linearization modeling technique, this paper deals with the velocity and power control of gas turbine in combined cycle power plant(CCPP) by multivariable generalized predictive control method. Then, a multivariable supervisory predictive control is proposed, which has been simulated in thermal power plant coordinated system. Third, this paper proposes a nonlinear multivariable supervisory predictive control. Neuro-fuzzy model is incorporated to represent the plant nonlinearity. In this way, constraints can still be tackled using Kuhn-Tucke condition. Gas turbine control is presented to illustrate the implementation and the performance of the proposed method. Comparative control studies suggest an improvement over conventional controller.