Title :
A nonlinear exponential ARX model-based multivariable generalized predictive control strategy for thermal power plants
Author :
Peng, Hui ; Ozaki, Toru ; Haggan-Ozaki, Valerie ; Toyoda, Yukihiro
Author_Institution :
Coll. of Inf. Eng., Central South Univ., Changsha, China
fDate :
3/1/2002 12:00:00 AM
Abstract :
Presents a modeling and control method for thermal power plants having nonlinear dynamics varying with load. First, a load-dependent exponential ARX (Exp-ARX) model that can effectively describe the plant nonlinear properties and requires only off-line identification is presented. The model is then used to establish a constrained multivariate multistep predictive control (ExpMPC) strategy whose effectiveness is illustrated by a simulation study of a 600 megawatt (MW) thermal power plant. Although the predictive control algorithm may be used without resorting to online parameter estimation, it is much more reliable, and displays much better control performance than the usual generalized predictive control (GPC) algorithm
Keywords :
autoregressive processes; multivariable control systems; nonlinear control systems; power station control; predictive control; steam power stations; 600 MW; 600 megawatt thermal power plant; load-dependent exponential model; nonlinear dynamics; nonlinear exponential ARX model-based multivariable generalized predictive control strategy; nonlinear properties; off-line identification; thermal power plants; Displays; Parameter estimation; Power generation; Power system reliability; Power system simulation; Prediction algorithms; Predictive control; Predictive models; Temperature control; Thermal loading;
Journal_Title :
Control Systems Technology, IEEE Transactions on
