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Rotor Speed Identification of PMSM on DTC System Based on PSO and CMAC Neural Network Algorithms

机译:基于PSO和CMAC神经网络算法的DTC系统PMSM转子转速辨识。

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Both the PSO (particle swarm optimization) for global search algorithm and the CMAC (cerebella model articulation controller) algorithm are used in the speed loop of direct torque control system in the permanent magnet synchronous motor.Firstly,the PSO algorithm is applied to search the optimal PID parameters in the domain space,and then the CMAC neural network is adopted to learn and train of the results which derive from the output of the PSO algorithm to furthermore optimize the PID parameters which can improve stability of the system.The DTC control system based on PSO with CMAC algorithmic and the traditional DTC (direct torque control) control system are established and simulated in the MATLAB circumstance whose results were all compared.It revels that the DTC control system based on PSO with CMAC algorithmic is fast response,ideal flux,and good anti-jamming.
机译:全局搜索算法的粒子群优化算法和小脑模型关节控制器的CMAC算法都用于永磁同步电动机直接转矩控制系统的速度环中。在域空间中优化PID参数,然后使用CMAC神经网络来学习和训练从PSO算法的输出中得出的结果,以进一步优化PID参数,从而提高系统的稳定性。在MATLAB环境下建立并仿真了基于CMAC算法的PSO的DTC控制系统,并对传统DTC(直接转矩控制)控制系统进行了仿真,并进行了仿真比较。结果表明,基于CMAC算法的PSO的DTC控制系统具有响应速度快,通量理想的特点。 ,并具有良好的抗干扰能力。

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