Parameter identification of BIPT system using chaotic-enhanced fruit fly optimization algorithm

Yuan, Xiaofang, Liu, Yuanming, Xiang, Yongzhong, Yan, Xinggang (2015) Parameter identification of BIPT system using chaotic-enhanced fruit fly optimization algorithm. Applied Mathematics and Computation, 268 . pp. 1267-1281. ISSN 0096-3003. (doi:10.1016/j.amc.2015.07.030)

Abstract

Bidirectional inductive power transfer (BIPT) system facilitates contactless power transfer between two sides and across an air-gap, through weak magnetic coupling. Typically, this system is nonlinear high order system which includes nonlinear switch components and resonant networks, developing of accurate model is a challenging task. In this paper, a novel technique for parameter identification of a BIPT system is presented by using chaotic-enhanced fruit fly optimization algorithm (CFOA). The fruit fly optimization algorithm (FOA) is a new meta-heuristic technique based on the swarm behavior of the fruit fly. This paper proposes a novel CFOA, which employs chaotic sequence to enhance the global optimization capacity of original FOA. The parameter identification of the BIPT system is formalized as a multi-dimensional optimization problem, and an objective function is established minimizing the errors between the estimated and measured values. All the 11 parameters of this system (Lpi, LT, Lsi, Lso, CT, Cs, M, Rpi, RT, Rsi and Rso) can be identified simultaneously using measured input–output data. Simulations show that the proposed parameter identification technique is robust to measurements noise and variation of operation condition and thus it is suitable for practical application.

Item Type: Article
DOI/Identification number: 10.1016/j.amc.2015.07.030
Uncontrolled keywords: Parameter identification; Fruit fly optimization algorithm (FOA); Bidirectional inductive power transfer (BIPT); Multi-dimensional optimization; Chaotic sequence
Subjects: T Technology
Divisions: Faculties > Sciences > School of Engineering and Digital Arts
Faculties > Sciences > School of Engineering and Digital Arts > Instrumentation, Control and Embedded Systems
Depositing User: Tina Thompson
Date Deposited: 01 Sep 2015 14:49 UTC
Last Modified: 29 May 2019 15:58 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/50349 (The current URI for this page, for reference purposes)
  • Depositors only (login required):

Downloads

Downloads per month over past year