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首页> 外文会议>2012 IEEE Student Conference on Research and Development >Fuzzy logic controller optimized by particle swarm optimization for DC motor speed control
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Fuzzy logic controller optimized by particle swarm optimization for DC motor speed control

机译：粒子群算法优化的模糊逻辑控制器对直流电动机的转速控制

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摘要

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.
机译：在本文中，我们提出了一种使用粒子群算法进行直流电动机速度控制的优化模糊逻辑控制器。使用MATLAB软件对控制器模型进行仿真，并在实验室直流电动机上进行实验测试。还比较了PID控制器，模糊逻辑控制器和优化的模糊逻辑控制器等不同控制器的性能。参考数字仿真和实验结果，所设计的FLC-PSO速度控制器与PID和常规FLC相比，具有更好的动态性能。而且，它可以获得直流电动机的卓越性能，并且还具有完美的速度跟踪而不会出现过冲。当启发式定义MF时，与常规模糊模型相比，显然优化成员函数（MF）能够提供更好的性能和更高的鲁棒性。此外，实验结果验证了所提出的FLC在负载转矩突然变化（导致速度变化）下的能力。

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