基于大脑情绪学习的PMLSM速度智能控制策略

P. Ghaebi Panah, A. Shafiei, A. Parsa Pour, B. Mirzaeian Dehkordi
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引用次数: 4

摘要

采用基于大脑情绪学习的智能控制(BELBIC)技术,设计了永磁直线同步电机(PMLSM)速度控制器。这是一个全面的非线性模型,包括非理想,如制动力,参数不确定性,不可预测的干扰和非线性摩擦。设计了一个比例积分(PI)控制器,并采用粒子群优化算法对其参数进行优化调整,作为评价方法性能的标准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Velocity control of a PMLSM using a brain emotional learning based intelligent control strategy
A velocity controller for a permanent magnet linear synchronous motor (PMLSM) is designed using a brain emotional learning based intelligent control (BELBIC). This is performed for a comprehensive nonlinear model of PMLSM including non-idealities such as detent force, parameter uncertainty, unpredicted disturbance, and nonlinear friction. As an evaluation criterion of the performance of the proposed method, a proportional - integral (PI) controller is designed whose parameters are optimally tuned by the particle Swarm Optimization (PSO) algorithm for better comparison.
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