| Summary: | 碩士 === 國立高雄第一科技大學 === 機械與自動化工程研究所 === 102 === This paper presents a new searching method for parameters’ identification of a nonlinear LCD glass-handling robot system by using an improved real-coded genetic algorithm (IRGA). It is well known that the real-coded genetic algorithm (RGA) method is an optimal or near optimal searching technique, which borrows the concepts from biological evolutionary theory. Furthermore, the selection of operators in the RGA is the key point to influence the final identified results. In this paper, three algorithm operators including the self-learning genetic algorithm (SLGA), adaptive real-coded genetic algorithm (ARGA) and terminal condition (TC) are combined to develop a new algorithm for system identification. The proposed algorithm is compared with various genetic algorithms, and the merits from numerical simulations and experimental results demonstrate that the proposed IRGA identification method is the best one and feasible for the glass-handling robot driven by a permanent magnet synchronous motor (PMSM).
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