Variable-structure control for a linear synchronous motor using a recurrent fuzzy neural network

Author(s): F.-J. Lin ; C.-H. Lin ; P.-H. Shen
DOI: 10.1049/ip-cta:20040489

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Author(s): F.-J. Lin ¹ ; C.-H. Lin ² ; P.-H. Shen ¹
- Affiliations: 1: Department of Electrical Engineering, National Dong Hwa University, Hualien, Taiwan
  2: Department of Electrical Engineering, National United University, Miao Li, Taiwan
Source: Volume 151, Issue 4, July 2004, p. 395 – 406
DOI: 10.1049/ip-cta:20040489 , Print ISSN 1350-2379, Online ISSN 1359-7035

A variable-structure controller, using a recurrent fuzzy neural network (RFNN) to control the mover position of a permanent-magnet linear synchronous motor (PMLSM) servo drive is developed. A variable-structure adaptive (VSA) controller is first adopted to control the mover position of the PMLSM, where a simple adaptive algorithm is utilised to estimate the uncertainty bounds. Then, to further improve the rate of convergence of the estimation, a variable-structure controller using an RFNN is investigated, in which the RFNN is utilised to estimate the real-time lumped uncertainty. Simulated and experimental results show that the proposed variable-structure controller using an RFNN provides high-performance dynamic characteristics and is robust with regard to plant-parameter variations and external disturbance. Furthermore, comparing with the VSA controller, a smaller control effort is required and the chattering phenomenon is reduced by the proposed variable-structure controller using an RFNN.

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Variable-structure control for a linear synchronous motor using a recurrent fuzzy neural network

Variable-structure control for a linear synchronous motor using a recurrent fuzzy neural network

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