Nonlinear model predictive control based on lexicographic multi-objective genetic algorithm

Author

Zheng Tao ; Wu Gang ; He De-feng

Author_Institution

Dept. of Autom., Univ. of Sci. & Technol. of China, Hefei

fYear

2007

fDate

25-28 Nov. 2007

Firstpage

61

Lastpage

65

Abstract

By using a series of dynamic coefficients in fitness function, a modified genetic algorithm is proposed. It can solve the lexicographic multi-objective optimization problem stemmed from multivariable nonlinear model predictive control directly. A control problem of a two-tank control system is then given as an example. Stair-like control strategy and feedback compensation are also used to develop a better performance of the controller. Simulation results verify the efficiency of the algorithm.

Keywords

compensation; feedback; genetic algorithms; multivariable control systems; nonlinear control systems; predictive control; feedback compensation; lexicographic multiobjective genetic algorithm; multivariable nonlinear model predictive control; stair-like control strategy; two-tank control system; Control systems; Electronic mail; Feedback; Genetic algorithms; Helium; Intelligent systems; Nonlinear dynamical systems; Predictive control; Predictive models; Process control;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent and Advanced Systems, 2007. ICIAS 2007. International Conference on

Conference_Location

Kuala Lumpur

Print_ISBN

978-1-4244-1355-3

Electronic_ISBN

978-1-4244-1356-0

Type

conf

DOI

10.1109/ICIAS.2007.4658348

Filename

4658348