A combination based control selection strategy for ultrasonic motor

Ultrasonic motors (USM) are a new type of high precision positioning drive system. They provide significant advantages compared to traditional electromagnetic motors like fast control, high torque, low electromagnetic interference and light weight. It is however difficult to formulate exact mathematical model of the ultrasonic motor due to complex nonlinearities involved as a result of its use of friction and inverse piezoelectric phenomena as its driving mechanism. These nonlinearities pose significant problem for precise position control of the motor. Previous research have therefore suggested developing control design using elaborate nonlinear control schemes like Sliding Mode Control (SMC) used in tandem with advanced machine learning algorithms like genetic algorithms. The drawback of implementing these approaches is the computational cost and complexity involved. In this paper we present a new schema for control of USM. We divide the problem into two complementary parts, namely estimation of the motors parameters and controller design based on the estimator result. Depending on the precision requirement of the application the estimation process can be made nonlinear and /or time varying. Similarly based on the affordable computational complexity, we can choose a linear or a nonlinear controller. Results of experiments conducted show the comparative performance of these different categories. Guidelines are suggested for suitable combination of them depending upon a user's requirement.