Nonlinear neural predictive control with control constraints

被引：0

作者：

Fu, ZG ^{[1
]}

Wang, SF ^{[1
]}

机构：

[1] Tsing Hua Univ, Dept Automat, Beijing 100084, Peoples R China

来源：

PROCEEDINGS OF THE 3RD WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-5 | 2000年

关键词：

neural element; neural model predictive control; stability; nonlinear programming;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a neural model is applied to predictive control and a Neural Model Constrained Predictive Control(NMCPC) algorithm for 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.

引用

页码：1081 / 1083

页数：3