Abstract
In order to get good performance of ultrasonic motors (USMs) in real applications, a real-time intelligent PID controller is proposed in this paper. To overcome the problems of characteristic variation and nonlinearity, an intelligent PID controller combined with particle swarm optimization (PSO) type neural network (NN) is studied in real-time environment for USM control. In the proposed method, an NN controller is designed for adjusting PID gains. The learning of NN is implemented by PSO updating the weights of NN on-line. By employing the proposed method, the characteristic changes and nonlinearity of USM can be compensated effectively in real-time environment. The effectiveness of the method is confirmed by experiments.
Highlights
As industrial technology develops in recent years, for actuators in industrial applications, there are more and more high requirements
A real-time intelligent PID control scheme combined with particle swarm optimization (PSO) type neural network (NN) has been proposed for ultrasonic motors (USMs)
NN is employed for optimizing the gains in PID controller
Summary
As industrial technology develops in recent years, for actuators in industrial applications, there are more and more high requirements. Ultrasonic motors (USMs), as a novel kind of actuators with perspective, are quickly developed. They are designed, improved and applied for meeting new and special requirements in many specific applications (1-3). In the field of USM control, there are many methods developed in recent years for compensating characteristic changes and nonlinearity (4-7). It is certified that intelligent control based on PID theory using NN is able to compensate characteristic changes and nonlinearity of USM in real applications. A real-time intelligent PID controller is reported as an extension of previous research. After this introduce section, the proposed intelligent PID controller is introduced in Sect.
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