Multiform optimization of predictive functional control based on Kautz model

Author

Xu, Mingzhu ; Jiang, Yiping ; Wen, Jie ; Pan, Cunzhi

Author_Institution

Coll. of Mech. Eng., Shijiazhuang Railway Inst., Shijiazhuang, China

fYear

2010

Firstpage

4982

Lastpage

4985

Abstract

There are five stochastic search algorithms had been designed to optimize the adaptive parameter in predictive functional controller based on Kautz model. They are exhaustive method, local search, particle swarm optimization, chaotic search and genetic optimization. The state stability condition for closed-loop system was given based on Lyapunov stability theory. Their validity had been verified by simulation, they can reduced online computation and presented strong robustness, and their optimize effect and consume were compared.

Keywords

Lyapunov methods; closed loop systems; genetic algorithms; nonlinear control systems; particle swarm optimisation; predictive control; stability; stochastic programming; Kautz model; Lyapunov stability theory; adaptive parameter optimization; chaotic search; closed loop system; exhaustion method; genetic optimization; local search; particle swarm optimization; predictive functional control; state stability condition; stochastic search algorithms; Algorithm design and analysis; Chaos; Optimization; Particle swarm optimization; Prediction algorithms; Predictive models; Stability analysis; Exhaustion method; Kautz model; Particle swarm optimization; Predictive functional control;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation (WCICA), 2010 8th World Congress on

Conference_Location

Jinan

Print_ISBN

978-1-4244-6712-9

Type

conf

DOI

10.1109/WCICA.2010.5554751

Filename

5554751