System Identification of an Induction Motor with Various Modeling by the Real-coded Genetic Algorithm

[[abstract]]本文的主要目的是利用機電系統的多種數學方程式所構成的感應馬達動態模型來識別馬達的參數。在動態建模時，我們做出一些假設來簡化動態模型。在系統鑑別時，我們使用實數編碼基因演算法（RGA）來尋找感應馬達在各種建模下的參數。RGA不但簡化了量測的步驟，而且也能快速得到馬達的參數。[[abstract]]The main objective of this paper is to identify the parameters of an induction motor, which is dynamically formulated by various mathematical models of the electromechanical system. In dynamic modelling, we make some assumptions to simplify the dynamic models. In system identification, we adopt the real-coded genetic algorithm (RGA) to find the parameters of various mathematical models of the induction motor. It can be successfully identified from the convergent fitness, and the identified parameters are compared and discussed. The RGA not only simplifies the measurement steps, but also quickly obtains the parameters