Title :
Nonlinear multivariable supervisory predictive control
Author :
Liu, X.J. ; Niu, L.X. ; Liu, J.Z.
Author_Institution :
Dept. of Autom., North China Electr. Power Univ., Beijing, China
Abstract :
The process of combined cycle power plant(CCPP) is characterized by nonlinearity and uncertainty. While model predictive control has been widely used in CCPP, incorporating of constraints is a major problem. Considering a supervisory control structure, this work presents nonlinear constraint predictive control by introducing of neuro-fuzzy networks(NFNs) representing a nonlinear dynamical process. Power and velocity control of gas turbine in CCPP is presented to illustrate the implementation and the performance of the proposed method. Comparative control studies suggest an improvement over conventional controller.
Keywords :
combined cycle power stations; fuzzy neural nets; gas turbines; multivariable control systems; neurocontrollers; nonlinear control systems; nonlinear dynamical systems; power control; predictive control; uncertain systems; velocity control; combined cycle power plant; gas turbine; neuro-fuzzy network; nonlinear dynamical process; nonlinear multivariable control; power control; supervisory predictive control; uncertain system; velocity control; Cost function; Economic forecasting; Nonlinear dynamical systems; Optimal control; Power generation; Power generation economics; Predictive control; Predictive models; Turbines; Velocity control;
Conference_Titel :
American Control Conference, 2009. ACC '09.
Conference_Location :
St. Louis, MO
Print_ISBN :
978-1-4244-4523-3
Electronic_ISBN :
0743-1619
DOI :
10.1109/ACC.2009.5160006
