Digital signal processor-based probabilistic fuzzy neural network control of in-wheel motor drive for light electric vehicle

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Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/107060

Title:	Digital signal processor-based probabilistic fuzzy neural network control of in-wheel motor drive for light electric vehicle
Authors:	林法正;Lin, F.-J.;Hung, Y.-C.;Hwang, J.-C.;Chang, I.-P.;Tsai, M.-T.
Contributors:	資訊電機學院電機工程學系
Keywords:	Applied sciences;Control systems;Control theory;Dynamical systems;Electric vehicles;Electrical engineering. Electrical power engineering;Electrical machines;Exact sciences and technology;Feedback;Miscellaneous;Motors;Networks;Nonlinear dynamics;Regulation and control
Date:	2012-02-01
Issue Date:	2026-04-23 13:54:54 (UTC+8)
Publisher:	Institution of Engineering and Technology;London: Institution of Engineering and Technology
Abstract:	摘要： A digital signal processor (DSP)-based probabilistic fuzzy neural network (PFNN) control is proposed in this study to control an in-wheel motor drive using a six-phase permanent magnet synchronous motor for light electric vehicle (LEV). First, the dynamics of LEV and in-wheel motor drive system with lumped uncertainty are described in detail. Then, a feedback linearisation control is designed to control the in-wheel motor drive system. Moreover, a non-linear disturbance observer is applied to estimate the lumped uncertainty for the designed feedback linearisation control. In order to achieve the required control performance of LEV, the PFNN control is developed for the control of the in-wheel motor drive system. The network structure and its on-line learning algorithm using delta adaptation law of the PFNN are derived. Moreover, a 32-bit fixed-point DSP, TMS320F2812, is adopted for the implementation of the proposed intelligent controlled drive system. Finally, some experimental results are illustrated to show the validity of the proposed PFNN control for in-wheel motor drive system. 出版者： London: Institution of Engineering and Technology 出版日期： 2012-02-01 出處： IET electric power applications, 2012-02, Vol.6 (2), p.47-61 資源來源： IET Digital Library Journals 版權： 2015 INIST-CNRS 版權： Copyright The Institution of Engineering & Technology Feb 2012 識別號： ISSN: 1751-8660 識別號： EISSN: 1751-8679 識別號： DOI: 10.1049/iet-epa.2011.0153
Appears in Collections:	[Department of Electrical Engineering] journal & Dissertation

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