| Summary: | 碩士 === 國立臺灣師範大學 === 工業教育研究所 === 92 === The object of this thesis is building the FDCMAC chip system with integrating Fuzzy Logical Controller (FLC) with Differentiable Cerebellar Model Articulation Controller (DCMAC). FLC is imitating fuzzy judgment of human. It uses the fuzzy knowledge base to descript controlling logic of controlled system. Compared with general controller, FLC is more robust and suitable. But FLC has some steady state error, and the time of building fuzzy knowledge base is very long by try and error. It couldn’t be accurate in control. With integrating DCMAC and FLC into FDCMAC, it can improve the disadvantage of FLC, shortening the time of building fuzzy knowledge base, enhancing the performance of FLC, reducing error of tracing system, and making accuracy rising. In this study, it uses the FPGA to implement FDCMAC chip system. FLC, DCMAC and the main control is designed on the FPGA. In designing FLC, we adopt the Mamdani method to be the method of fuzzy inference. In designing DCMAC, we adopt lookup-table of Gauss function. And we design parallel FLC and DCMAC computing capability on FPGA by Verilog HDL. Finally, the FDCMAC chip system will experiment on controlling linear piezoelectric ceramic motor (LPCM) to prove that it has good performance of control.
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