基于灰色预测理论的DTC模糊控制器优化设计

Optimal design of DTC fuzzy controller based on grey prediction theory

针对常规模糊控制器在直接转矩控制过程中因电机模型参数不变、滞后所带来的超调量大、响应慢和不稳定性等问题,采用预测模糊控制的方法,通过电机参数预测模型得出下一状态磁链、转矩和磁链位置角,经过模糊推理给出相应的最佳或次最佳控制方案.仿真结果表明,采用灰色预测模糊控制方法的直接转矩控制系统能够克服滞后效应对系统的影响,使调节过程平稳.在动态响应、抗干扰能力和鲁棒性等方面取得了良好的效果,其控制精度及动态品质均优于常规的模糊控制器.

To solve such problems as big overshoot, slow response and unsteadiness caused by parameter invariance and time delay of motor model in direct torque control （DTC） of the traditional fuzzy controllers, the magnetic chain, torque and flux oriented angle were gained based on grey prediction theory. The optimal control scheme was given through fuzzy inference. The simulation results show that the proposed method can avoid the influence of time delay on the system and ensure the steadiness of the adjusting process. The system can exhibit more satisfactory dynamic response, anti-interference and robustness. The grey prediction fuzzy controller in DTC system has good performance and is more effective than the traditional fuzzy controller.