本論文主要研究目的為利用提出之雙輸入雙輸出小波模糊類神經網路控制器結合新型每安培最大轉矩控制法應用於內藏式永磁同步馬達驅動系統以改善馬達效率，並藉由加入改良型干擾轉矩觀測器改善在週期性變動負載干擾下之速度響應。為使馬達控制系統在參數變化和外來干擾的影響下具備強健之控制性能，使用本論文提出之雙輸入雙輸出小波模糊類神經網路控制器，線上調整馬達參數，再透過改良型干擾轉矩觀測器提供前饋補償控制力。新型每安培最大轉矩控制法是以磁場導向控制法為基礎來發展，藉由訊號注入之概念將訊號注入至電流角度上造成功率擾動進而提供電流角度讓馬達運作在最佳操作點上。本論文亦提出具線上增益調變之最佳速度迴路頻寬之馬達伺服驅動器架構，同樣利用提出之雙輸入雙輸出小波模糊類神經網路線上調整參數來改善頻寬大小。最後透過微芯公司(Microchip)所生產之數位訊號處理器實現內藏式永磁同步馬達驅動系統，透過模擬以及在測試平台上實測並驗證其有效性、可行性和在負載轉矩干擾下擁有良好的速度響應。;A novel maximum torque per ampere (MTPA) method based on power perturbation for a field-oriented control (FOC) interior permanent magnet synchronous motor (IPMSM) drive system is proposed in this study. The proposed MTPA method, which is parameter independent and can improve the motor operation at both start-up and low speed, is designed based on the power perturbation by using the signal injection in the current angle. Moreover, the influence of current and voltage harmonics to the MTPA control can be eliminated effectively. Furthermore, to enhance the robustness of the control system, an online tuning scheme for an integral-proportional (IP) controller using a new wavelet fuzzy neural network (WFNN) with disturbance torque feedforward control is developed where the disturbance torque is obtained from an improved disturbance torque observer also proposed in this study. In order to achieve an optimal bandwidth, a novel online auto-tuning technique also using the new wavelet fuzzy neural network (WFNN) for a field-oriented control (FOC) interior permanent magnet synchronous motor (IPMSM) servo drive is proposed in this study. Finally, some experimental results using an IPMSM drive system based on a low price digital signal processor (DSP) are presented. From the experimental results, the proposed control approach can guarantee the control performance of speed loop even under a cyclic fluctuating load.
