Servo position control of ultrasonic motors using fuzzy neural network

With their significant advantages over traditional electromagnetic motors, ultrasonic motors (USMs) are becoming attractive for mechatronic applicatio ns. Since USMs suffer from a lack of applicable mathematical model while th eir speed characteristics are heavily nonlinear and time varying, it used t o be difficult to apply them for servo application. This paper presents a f uzzy ne ural network controller for servo position control of an USM. It co mbines both the knowledge-based fuzzy logic and the learning-incorporated n eural network. As a result, it compensates the nonlinear behavior of the mo tor and optimizes its performance on-line. To further improve the motor per formance, both of their control inputs, namely the driving frequency and ph ase difference of the 2-phase inverter waveforms, are employed. Experiments are then performed for various reference inputs. The results demonstrate s uperiority of the controller in terms of tracking and steady-state performa nce.