研究了一种使用改进的蚁群算法(ACA,Ant colony algorism)对模糊PID控制器进行优化的设计方法；针对模糊PID控制器难以应对电机高性能速度跟踪以及控制精度不高且鲁棒性差的缺点,提出了一种新的自适应电机控制器设计方法；首先建立永磁同步电机的数学模型和优化后的控制器模型,然后引入改进的ACA算法对PID控制器3个比例参数进行全局优化,并定义了优化的具体算法以实现对参数的优化整定；为了验证文中方法的有效性,通过Matlab仿真工具对电机控制实例进行仿真验证,结果表明,文中控制器能克服模糊PID控制器的不足,具有很强的鲁棒性和快速响应性能,能很好地适应负载的变化.%A method for combing the improved ACA (Ant colony algorism) and PID control used for controlling PMSM (Permanent manage synchronous motor) is researched. Aiming at conquering the defects of low control precision and the robustness of fuzzy PID control, a new control is designed. Firstly, the mathematical model of PMSM is defined, the improved ACA optimize algorism is used to optimize the three parameters of fuzzy PID control, and the optimizing algorism is described. Finally, the Matlab tool is used to simulate the control instance. The experiment result shows the method in our paper can conquer the defects of fuzzy PID control, has the strong robustness and rapid response ability, can suit the dynamic changed load.
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