基于神经网络的自适应模糊控制在交流调速中的应用研究

Application of Neural-network-based Self-adaptive Fuzzy Control in AC Speed Adjustment

针对现代的交流调速系统中存在的问题,充分利用神经网络的自学习自适应能力和快速计算能力,提出了一种用径向基函数(RBF)神经网络来实现的具有在线自调整功能的模糊控制方案,并给出了把神经网络和模糊控制器相结合的基本设计方法.通过实际交流调速系统的实验表明,该控制方案与传统的PID控制相比,具有鲁棒性强、恢复时间断和超调量小等特点.

For the existing problem of modern AC speed adjustment, full use is made of NN' features, such as self study ,adaptation and fast computing ability, a self-adaptive fuzzy control algorithm is given based on NN of RBF,besides ,the method to construct NN and fuzzy controller is given. Through experiment of actual AC-speed adjustment system, this algorithm contrast with PID control has such qualities as strong robustness,quick response, diminutive overshot,and so on.