Model Predictive Control for Max-Plus-Linear Systems: Linear Programming Solution

Author

Zou, Yuanyuan ; Li, Shaoyuan

Author_Institution

Inst. of Autom., Shanghai Jiao Tong Univ.

Volume

1

fYear

0

fDate

0-0 0

Firstpage

339

Lastpage

343

Abstract

Hybrid systems receive a lot of attention from both the computer science and the control community in recent years. The max-plus-linear (MPL) system is a typical subclass of hybrid systems. In this paper, we extend model predictive control (MPC) framework to the MPL system. We present a new optimization method for MPL-MPC problem that is based on canonical forms for max-min-plus-scaling (MMPS) functions (using the operations maximization, minimization, addition and scalar multiplication) with linear constraints on the inputs. This method is more efficient than applying nonlinear optimization that was done in previous work

Keywords

linear programming; minimax techniques; minimisation; predictive control; addition; hybrid systems; linear constraints; linear programming; max-min-plus-scaling functions; max-plus-linear systems; maximization; minimization; model predictive control; optimization; scalar multiplication; Computer aided manufacturing; Constraint optimization; Control systems; Linear programming; Mathematical analysis; Mathematical model; Optimization methods; Power system modeling; Predictive control; Predictive models; canonical form; hybrid systems; linear programming; max-min-plus-scaling function; max-plus-linear systems; model predictive control;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1712329

Filename

1712329