本論文研究的目的是研製與發展以數位訊號處理器為基礎之智慧型錯誤容忍控制六相永磁同步馬達驅動系統，其適用於電動載具及電動機需持續運轉之特殊應用場合。六相永磁同步馬達驅動系統為高度非線性之系統，且對於系統參數變化和外來干擾相當敏感，尤其是發生馬達繞組斷線或是反流器故障時，不平衡電流將使馬達轉矩抖動，導致馬達無法平順運轉，故提出錯誤偵測與運轉決策判斷方法，以防止馬達造成進一步擴大毀損。然而系統穩定性與錯誤容忍控制為六相永磁同步馬達驅動控制系統最重要的發展議題，因此本論文提出以下兩種智慧型控制系統：非對稱歸屬函數之TSK型模糊類神經網路控制器和智慧型互補式滑動模態控制器，以改善控制性能，且達到錯誤容忍控制六相永磁同步馬達驅動系統之穩定性要求。本論文將詳細介紹智慧型控制的架構以及線上學習法則，最後以DSP (TMS320F28335)實現六相永磁同步馬達驅動系統，並且以實驗結果驗證所提出方法之可行性。

The objective of this thesis is to develop and implement a digital signal processor (DSP) based fault tolerant control of six-phase permanent magnet synchronous motor (PMSM) drive system. This system is suitable for industrial applications such as mechanical tools, electric vehicles and some specific applications. The six-phase PMSM drive system is highly nonlinear and is very sensitive to parameter variations and external disturbance. When the motor winding or the respective inverter is broken, the torque fluctuation will appear due to unbalanced current and the motor will operate under non-smooth situation. Therefore, the fault detection and operating decision method is proposed in the thesis to prevent serious broken. Since, the stability and the fault tolerant control are the most important issues of the six-phase PMSM drive and control system, therefore, two intelligent control systems, which can improve the control performance and the requirements of stability of fault tolerant control of six-phase PMSM drive system, are proposed: a Takagi-Sugeno-Kang type fuzzy neural network with asymmetric membership function (TSKFNN-AMF) controller and an intelligent complementary sliding-mode controller (ICSMC). The network structure and the online learning algorithms of the intelligent controller are introduced in detail. Moreover, the proposed control systems are implemented in a TMS320F28335 DSP to verify the feasibility of the proposed control schemes.

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