直流無刷馬達之適應性模糊滑動模式位置控制

Adaptive Fuzzy Sliding Mode Position Control of a Brushless DC Motor

董義雄(I-Shun Dong)

指導教授 ： 賴玲瑩

中原大學/工學院/電機工程研究所/碩士(2003年)

https://doi.org/10.6840/cycu200300110

摘要

本文探討模糊滑動模式控制法則(Fuzzy Sliding Mode Controller，簡稱FSMC)應用於直流無刷旋轉馬達位置控制之可行性。直流無刷旋轉馬達的系統參數具有隨輸入命令不同而微量改變的特質，而FSMC對於受控體模型不精確的情況下亦能達到良好的輸出響應。本文之控制法則的架構是以模糊控制結合滑動模式控制為主。而在控制法則之最佳化部分，乃同時將模糊規則庫及控制法則的增益值皆納入搜尋，並以適應性基因演算法(Adaptive Genetic Algorithm，簡稱AGA)進行參數搜尋的工作，其適應性交配率與突變率公式可避免落入區域極值而加速收斂。模擬部分使用套裝軟體Matlab/Simulink予以實現。實驗部分使用俊原科技所提供的直流無刷旋轉馬達搭配功率放大器、TI DSP(TMS320F243)控制器加以驗證本文控制法則的可行性。結果顯示，FSMC在馬達參數變動的情況下具有高強健性，而以AGA設計之最佳FSMC將可快速地追隨到位置命令。

關鍵字

模糊控制 ； 適應性基因演算法 ； 滑動模式控制

並列摘要

Investigated in this thesis is the feasibility of using Fuzzy Sliding Mode controller (FSMC) for position control of DC brushless rotary Motor. The parameters of DC brushless rotary Motor will change slightly with different input command. And FSMC can achieve good output response even when the plant model has some uncertainty. The structure of the control algorithm in this thesis is to combine fuzzy control with sliding mode control. And in the optimization part of the control algorithm, the 3*3 fuzzy rule base and the gains of the control algorithm are searched simultaneously through adaptive genetic algorithm (AGA), whose adaptive crossover rate and mutation rate can avoid falling into local optimum and speed up the convergence. The simulation part of the control algorithm design is done through the software of Matlab/Simulink. As for the experiment part, we use the DC brushless rotary Motor, power amplifier and TI DSP (TMS320 F243) controller supported by Juniortek to verify and improve the feasibility of controller. The results show that, FSMC is highly robust even when the plant model has some uncertainty, and the optimal FSMC designed by AGA can track position command rapidly.

並列關鍵字

Adaptive Genetic Algorithm ； Sliding Mode Control ； Fuzzy Control

參考文獻

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