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A Novel Inertia Identification Method for Servo System Using Genetic Algorithm

机译：基于遗传算法的伺服系统惯性识别新方法

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摘要

To improve the dynamic response characteristics of permanent magnet synchronous motor (PMSM) servo system, an inertia identification method based on the theory of model reference adaptive system (MRAS) has been researched. A novel inertia identification method using genetic algorithm (GA) is proposed for requirements of rapid convergence and high precision. This method takes advantage of the global search capability of GA, taking deviation between actual angular velocity and estimated angular velocity as control error, utilizing integral of time multiplied absolute value of error (ITAE) as optimized target, dynamically adjusting adaptive gain of MRAS, to achieve optimization of control parameters on-line. Experimental results proved that this method has a faster convergence rate and a higher precision in inertia identification, confirmed effectiveness and feasibility of this method.
机译：为了提高永磁同步电动机（PMSM）伺服系统的动态响应特性，研究了一种基于模型参考自适应系统（MRAS）理论的惯性辨识方法。针对快速收敛和高精度的需求，提出了一种基于遗传算法的惯性识别方法。该方法利用GA的全局搜索能力，将实际角速度和估计角速度之间的偏差作为控制误差，利用时间乘以误差的绝对值（ITAE）的积分作为优化目标，动态调整MRAS的自适应增益，从而在线实现控制参数的优化。实验结果表明，该方法收敛速度更快，惯性识别精度更高，证明了该方法的有效性和可行性。

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