Loughborough University
Browse

File(s) under permanent embargo

Reason: This item is currently closed access.

An enhanced approach for parameter estimation: using immune dynamic learning swarm optimization based on multicore architecture

journal contribution
posted on 2016-09-28, 10:46 authored by Zhao-Hua Liu, Xiao-Hua Li, Hong-Qiang Zhang, Liang-Hong Wu, Kan Liu
The identification of physical parameters is crucial for control system designs, condition monitoring and fault diagnosis of industrial drive systems. The article brings multicore architecture based parallel computing technology and bioinspired intelligent optimisation algorithm insight into designing for system parameter estimation models.models. In this study, a parallel implementation using an immune-cooperative dynamic learning particle swarm optimization (PSO) algorithm with multicore computation architectures is presented for permanent magnet synchronous machine (PMSM) parameter estimations. Three novel strategies are discussed, all with the purpose of enhancing the dynamic response and fast convergence performance of the designed parameter estimator. The strategies include a dynamic velocity modification strategy, an immune-memory-based searched information preservation mechanism, and an immune-network-based learning operator for PSO. Finally, a proposed method is applied to the parameter estimations of PMSMs as well as parallel running on multicore central processing units (CPU).

Funding

This work was supported in part by the National Natural Science Foundation of China under Grant (51374107, 61503134, 51577057, 61573299), the China Postdoctoral Science Foundation funded project under Grant (2013M540628, 2014T70767), and the Hunan Provincial Education Department outstanding youth project under Grant (15B087).

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IEEE Systems, Man, and Cybernetics Magazine

Volume

2

Issue

1

Pages

26 - 33

Citation

LIU, Z.-H. ... et al, 2016. An enhanced approach for parameter estimation: using immune dynamic learning swarm optimization based on multicore architecture. IEEE Systems, Man, and Cybernetics Magazine, 2 (1), pp. 26-33.

Publisher

© IEEE

Version

  • VoR (Version of Record)

Publication date

2016-06-07

Notes

This paper is in closed access.

eISSN

2333-942X

Language

  • en