Fuzzy logic controller optimized by particle swarm optimization for DC motor speed control

R. Rahmani, M. Mahmodian, S. Mekhilef, A. Shojaei
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引用次数: 17

Abstract

In this paper, we presented an optimized fuzzy logic controller using particle swarm optimization for DC motor speed control. The controller model is simulated using MATLAB software and also experimentally tested on a laboratory DC motor. A comparison of the performance of different controllers such as PID controller, fuzzy logic controller and optimized fuzzy logic controller is presented as well. With reference to the results of digital simulations and experiment, the designed FLC-PSO speed controller obtains much better dynamic behavior compared to PID and the normal FLC designed. Moreover, it can acquire superior performance of the DC motor, and also perfect speed tracking with no overshoot. The optimized membership functions (MFs) are obviously proved to be able to provide a better performance and higher robustness in comparison with a regular fuzzy model, when the MFs were heuristically defined. Besides, experimental results verify the ability of proposed FLC under sudden change of the load torque which leads to speed variances.
基于粒子群优化的模糊控制器用于直流电机转速控制
本文提出了一种基于粒子群优化的模糊控制器,用于直流电动机速度控制。利用MATLAB软件对控制器模型进行了仿真,并在实验室直流电机上进行了实验测试。并对PID控制器、模糊控制器和优化模糊控制器的性能进行了比较。数字仿真和实验结果表明,所设计的FLC- pso速度控制器与PID和普通FLC相比具有更好的动态性能。不仅可以获得直流电动机的优良性能,而且可以实现良好的速度跟踪,无超调。结果表明,当启发式定义隶属函数时,优化后的隶属函数比常规模糊模型具有更好的性能和鲁棒性。此外,实验结果验证了所提出的FLC在负载转矩突变导致速度变化的情况下的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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