Predictive functional control based on differential evolution algorithm and its dynamic performance analysis

Author

Xiao-Ping, Ma ; Ya-Peng, Li ; Pi-zhao, Su ; Feng-shuan, An

Author_Institution

Sch. of Inf. & Electr. Eng., China Univ. of Min. & Technol., Xuzhou, China

fYear

2010

fDate

26-28 May 2010

Firstpage

65

Lastpage

68

Abstract

An optimization method of predictive function control (PFC) parameters that based on modified differential evolution (DE) is provided. Differential evolution is a new evolutionary computation technology and exhibits good performance on optimization. Differential evolution algorithm as a relatively new evolutionary computation technique has a good optimization. Therefore, the modified differential evolution which is proposed to solve the optimization problems. The new algorithm uses initialization and the scale factor and crossover probability to improve PFC control performance in terms of model mismatch and parameters optimization. Simulation results show that the performance of the optimized DE PFC controller is superior to that of the conventional PFC controller.

Keywords

evolutionary computation; predictive control; probability; crossover probability; differential evolution algorithm; dynamic performance analysis; evolutionary computation technology; parameter optimization; predictive functional control; Electrical equipment industry; Evolutionary computation; Heuristic algorithms; Optimization methods; Performance analysis; Predictive models; Production; Real time systems; Robust control; Robust stability; PFC; crossover probability; differential evolution algorithm; scale factor;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (CCDC), 2010 Chinese

Conference_Location

Xuzhou

Print_ISBN

978-1-4244-5181-4

Electronic_ISBN

978-1-4244-5182-1

Type

conf

DOI

10.1109/CCDC.2010.5499128

Filename

5499128