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AC Servo System Based on MEC Optimization and Fuzzy Neural Network Control

机译:基于MEC优化和模糊神经网络控制的交流伺服系统

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To satisfy the requirements of higher accuracy and faster response in AC servo system, a system with a fuzzy neural network controller based on mind evolutionary computation (MEC) optimization was designed. The controller combined the advantage of fast searching optimization of MEC and the advantage of not depending on controlled plant of fuzzy neural network controller. This method uses MEC to search the optimal mean, the optimal standard deviation and the optimal weights that connect membership layer and rule layer. Simulation and experimental results verified the effectiveness of the method. The results show that this method has good control effect on both system regulating and set-point following. For AC system in practice, this method has quite good disturbance resistance and strong robustness, and both dynamic and steady performances were improved evidently.
机译:为了满足AC伺服系统的更高精度和更快的响应的要求,设计了一种基于思维进化计算(MEC)优化的模糊神经网络控制器的系统。控制器组合了快速搜索MEC的优化以及不取决于模糊神经网络控制器的受控植物的优势。该方法使用MEC来搜索最佳平均值,最佳标准偏差和连接成员层和规则层的最佳权重。仿真和实验结果验证了该方法的有效性。结果表明,该方法对两个系统调节和置位进行了良好的控制效果。对于AC系统在实践中,该方法具有相当良好的扰动和强大的稳健性,并且动态和稳定的性能显然得到了改善。

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