在新型的超音波馬達裡，尤其是旋轉駐波型超音波馬達，在工業、消費者、機械人與汽車的伺服系統應用層面裡，直接驅動的致動器已經受到高度重視。超音波馬達擁有許多獨特的優點，像是低轉速高扭力、體積小、運轉安靜以及沒有電磁干擾的問題，適合應用在窗簾或是辦公室等安靜的場所使用。
在超音波馬達的驅動器上，最常用的有二相半橋串聯共振、電流源並聯共振以及串並聯(LLCC)共振變頻器等等。這些變頻器在操作時同時存在著優缺點。串聯共振與並聯共振容易受到品質因素的影響。而串並聯共振變頻器則是沒有品質因素干擾的問題。本論文是採用以串並聯共振架構的非對稱脈波寬度調變變頻器(APWM)用來驅動超音波馬達。當此變頻器操作在超音波馬達的共振頻率時，能夠減少二次和高次諧波的干擾以及在電晶體開關的切換上達到零電壓切換，減少切換損失並且輸出二相電壓振幅不隨著頻率變動而有所不同。因此，利用APWM共振變頻器，超音波馬達能夠維持良好的性能。
超音波馬達的特性是複雜且高度非線性，因此傳統的PI控制器在不穩定的系統裡很難有較佳的性能，容易受到負載干擾使系統更不穩定。本篇論文採用了新穎的遞迴類神經網路控制器，在陌生或是不明確的系統裡，透過即時學習與自我修正機制，克服外在因素之干擾，達到即時控制之目的，使系統能有更強健的控制效能。因此在超音波馬達的速度控制上，選用遞迴類神經網路控制器會比傳統的PI控制器有更良好的性能產生。
最後，由實驗結果可以證明，負載干擾的存在與否，遞迴類神經網路控制器都比傳統PI控制器展現出較佳的性能；而且所採用的非對稱脈波寬度調變變頻器在驅動超音波馬達上也有良好的效能。

The newly ultrasonic motor (USM), especially the rotary traveling-wave type, has invited special interest as direct drive type actuators for servo systems in industrial, consumable, robotic and automotive applications. The USM has many outstanding features such as high torque at low speed, compactness in size, silence and no electromagnetic interferences.
Several driving circuits for the USM generally include the two-phase half-bridge series-resonant inverter, the current-source parallel-resonant inverter, the LLCC resonant inverter, and so on. The advantages and drawbacks are existed simultaneously under those circuits operating. This thesis adopted the asymmetrical-pulsed-width-modulated (APWM) inverter which is based on the LLCC resonant topology for driving the USM. When the APWM inverter is operated near the resonant frequency, the second and high-order harmonics of the inverter can be reduced and the zero-voltage-switching both at turn-on and turn-off of the transistor also can be achieved. Then a good performance can be maintained.
The control characteristics of the USM are so complex and highly nonlinear that the conventional PI controller is hard to control the uncertain system. The novel recurrent neural network (RNN) controller provide a way for the design of online control for drive systems having unknown or uncertain dynamics.
Finally, between the conventional PI controller and the proposed RNN controller, results of this study showed a superior performance for controlling the USM; and the proposed inverter has a good achievement for driving the USM.

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