Design and Implementation of Motor Control Systems Using Intelligent-Based Controller

• Main Authors: Ke-Han Wu, 吳科翰
• Other Authors: Der-Fa Chen
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/16615233233934648528

碩士 === 國立彰化師範大學 === 工業教育與技術學系 === 99 === This purpose of this study was to construct a simulate control system of digital motor designed with a controller as well as to explore it’s operation situation actually. The system was composed of powerful simulate software,VisSim,featured simulate immediately, high compatibility, easy to learn and so on. The subject of the controller was the adaptive controller. Besides, the parameter value theory to estimate of the adaption law was to simulate the thinking process while people facing the unknown question. Firstly, all possible ways was sought in widespread through lateral thinking. Secondly, the possible formula to solute was selected with vertical thinking. On the one hand, lateral thinking process was accomplished from the classificatory value of neural controllers and the predicted data of gray predictor controller. On the other hand, vertical thinking process was completed by the fuzzy controller to logical deduced and got the estimated approximate value. Thirdly the estimated approximate value was tested in the system. After the research was examined its function and the accuracy of estimative approximate value in order to established the reference model, the step test signals were both set in reference model and real model. At the same time, the error between each other was nearly zero. Finally, the adaptive controller of strengthened no load and the adaptive controller of strengthened load were both tested their variation of output. Because the speed of load system’s output so rapid that caught up with its input of reference signals, the controller was confirmed its properties such as practical and robust. To compare with adaptation law derived, the accuracy of estimated value was closer to the true model; therefore, the pondering rule of the research was proved practicability.