Title :
Nonlinear neural predictive control with control constraints
Author :
Zhigang, Fu ; Wang Shifu
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
Abstract :
A neural model is applied to predictive control and a neural model constrained predictive control (NMCPC) algorithm for a nonlinear process is proposed. In this algorithm, the neural model and nonlinear programming by gradient optimization are combined to obtain the optimal control law. The simulation result shows that NMCPC could achieve satisfactory control performance
Keywords :
gradient methods; neurocontrollers; nonlinear control systems; nonlinear programming; optimal control; predictive control; control constraints; gradient optimization; neural model constrained predictive control; nonlinear neural predictive control; nonlinear process; optimal control law; Optimal control; Prediction algorithms; Predictive control; Predictive models; Stability;
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location :
Hefei
Print_ISBN :
0-7803-5995-X
DOI :
10.1109/WCICA.2000.863405
