本論文是將一般針對超音波馬達(Ultrasonic Motor)系統的線性非時變特性進行非線性摩擦力之研究。雖然超音波馬達與一般馬達架構上不同,但是其摩擦力模型與傳統馬達的摩擦力模型相似。為了求得摩擦力模型之參數且最佳化,本文研究粒子群演算法(PSO)與電荷演算法(CSS)來進行鑑別系統,並比較其摩擦力模型參數之正確性。 在控制器方面,本文分別研究non-model based控制器與model based 控制器。其中non-model based控制器使用倒傳遞類神經網路來進行追蹤軌跡之即時控制器設計。model based控制器則是使用前饋控制器來消除系統摩擦力所導致的定位誤差,再以高增益觀測器解決了微分上不連續的情形以及干擾觀測器抵抗外在的干擾以達到精密定位系統之要求,最後以順滑模態控制器取代傳統的PID控制器,更能增強系統的強健性。為了驗證本文所提出控制器對於模型不確定與外擾的強健性,最後使用兩個即時追蹤任務進行兩種控制器之比較研究。
The purpose of this paper is to investigate the nonlinear friction and compensation for a piezoelectric ceramic ultrasonic motor (USM). Although the architecture of the USM is different from the general electric-mechanical motor, the mathematic model for the USM motor can use the same friction model to formulate the friction phenomenon. To establish the feedforward controller, the system identification for the USM is needed to study to design the model-based controller. To obtain the optimal system parameters of the USM, PSO and CSS algorithms are studied to identify the system parameters for the nonlinear friction model. For the controller design, a non-model based controller, using back-propagation neural network controller to trace the track, and the model-based controller, which consists of the feedforward controller based on the system identification and the sliding-mode control, are discussed in this paper. Finally, the two real-time tracking tasks are used to validate the proposed method.