A RECEDING-HORIZON REGULATOR FOR NONLINEAR-SYSTEMS AND A NEURAL APPROXIMATION

被引：236

作者：

PARISINI, T ^{[1
]}

ZOPPOLI, R ^{[1
]}

机构：

[1] UNIV GENOA,DEPT COMMUN COMP & SYST SCI,DIST,I-16145 GENOA,ITALY

来源：

AUTOMATICA | 1995年 / 31卷 / 10期

关键词：

OPTIMAL CONTROL; NONLINEAR SYSTEMS; RECEDING HORIZON REGULATORS; STABILIZATION; NEURAL NETWORKS;

D O I：

10.1016/0005-1098(95)00044-W

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A receding-horizon (RH) optimal control scheme for a discrete-time nonlinear dynamic system is presented. A nonquadratic cost function is considered, and constraints are imposed on both the state and control vectors. Two main contributions are reported. The first consists in deriving a stabilizing regulator by adding a proper terminal penalty function to the process cost. The control vector is generated by means of a feedback control law computed off line instead of computing it on line, as is done for existing RH regulators. The off-line computation is performed by approximating the RH regulator by means of a multilayer feedforward neural network (this is the second contribution of the paper). Bounds to this approximation are established. Simulation results show the effectiveness of the proposed approach.

引用

页码：1443 / 1451

页数：9

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