Title :
A new kind of nonlinear model predictive iterative learning control
Author :
Wang, Jinyi ; Liu, Xiangjie
Author_Institution :
State Key Lab. of Alternate Electr. Power Syst. with Renewable Energy Sources, North China Electr. Power Univ., Beijing, China
Abstract :
A nonlinear model predictive controller based on iterative learning control (NMPILC) is proposed. The nonlinear plant dynamic is described by a fuzzy model which contains local liner models. Based on this model, model predictive control algorithm that utilizes past data along with real-time measurements is devised. This algorithm is developed to address the learning rate for a class of repetitive system with non-repetitive disturbances. The iterative learning control law is given. It is shown that the control performance of the proposed NMPILC can be greatly improved by using this on-linear model predictive iterative learning control algorithm.
Keywords :
fuzzy set theory; iterative methods; learning systems; nonlinear control systems; predictive control; NMPILC; fuzzy model; iterative learning control law; learning rate; local liner models; nonlinear model predictive controller; nonlinear plant dynamic; nonrepetitive disturbances; real-time measurements; repetitive system; Convergence; Covariance matrix; Mathematical model; Prediction algorithms; Predictive control; Predictive models; Trajectory; Fuzzy model; Iterative Learning Control (ILC); Model Predictive Control (MPC);
Conference_Titel :
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4577-2073-4
DOI :
10.1109/CCDC.2012.6244228
