Title :
A novel identification method based on QDPSO for Hammerstein error-output system
Author :
Du, Zhiyong ; Wang, Xianfang
Author_Institution :
Henan Mech. & Electr. Eng. Coll., Xinxiang, China
Abstract :
The objectives of this paper are to identify the Hammerstein system adaptively based on Quantum Delta-potential-well-based Particle Swarm Optimization(QDPSO). First, the Hammerstein output-error system is shown in briefly. Second, according to the article Swarm Optimization(PSO), an improved QDPSO algorithm is presented. Third, training samples for intermediate linear model are obtained by operating measured data synthetically, and coefficients of the intermediate model is obtained by the QDPSO algorithm. Finally, The efficiency of the proposed algorithm is demonstrated by simulation examples.
Keywords :
identification; nonlinear systems; particle swarm optimisation; Hammerstein error output system; QDPSO; identification method; particle swarm optimization; quantum delta potential well; Chemical elements; Computer errors; Control engineering; Educational institutions; Evolutionary computation; Information technology; Nonlinear systems; Parameter estimation; Particle swarm optimization; Temperature measurement; Hammerstein Error-output System; Parameter Identification; Particle Swarm Optimization; Quantum Delta-potential-well-based PSO;
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
DOI :
10.1109/CCDC.2010.5498600
