NDLI: Parameter approximate dynamic optimization for PSO systems

Content Provider	IEEE Xplore Digital Library
Author	Qi Kang Lei Wang Derong Liu Qidi Wu
Copyright Year	2009
Description	Author affiliation: Key Laboratory of Complex Systems and Intelligence Science, Chinese Academy of Sciences, Beijing 100190, China (Derong Liu) \|\| College of Electronics and Information Engineering, and the Key Laboratory of Embedded System and Computer-service of MOE, Tongji University, Shanghai 201804, China (Qi Kang; Lei Wang; Qidi Wu)
Abstract	This paper presents a novel swarm approximate dynamic programming method (swarm-ADP) for parameter optimization of PSO systems, from the perspective of optimal control. Based on the stability results of a simplified PSO and the swarm-ADP algorithm, parameter dynamic optimization and computation is studied in detail for a deterministic PSO system and a stochastic PSO system, respectively. Furthermore, numerical simulations based on several benchmarks optimization are performed. The results show the validity of the proposed parameter optimization method for PSO systems.
Starting Page	5003
Ending Page	5008
File Size	1757860
Page Count	6
File Format	PDF
ISBN	9781424438716
ISSN	01912216
DOI	10.1109/CDC.2009.5400841
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Signal processing algorithms Approximation algorithms Stochastic processes Stochastic resonance Upper bound Estimation error Multidimensional systems Adaptive control Stochastic systems Software algorithms
Content Type	Text
Resource Type	Article

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