Title :
Intelligent PID control based on PSO type NN for USM
Author :
Shenglin Mu ; Tanaka, K. ; Nakashima, S. ; Alrijadjis, D. ; Tomimoto, H.
Author_Institution :
Electron. Control Dept., Hiroshima Nat. Coll. of Maritime Technol., Hiroshima, Japan
Abstract :
Ultrasonic Motors (USMs) are a kind of actuators with attractive features. Owing to the features, they are expected to be applied widely in industrial fields. Especially, since they work well in or near MRI environment, they are expected to play more important roles in medical and welfare area. In this research, for the control of USM, an intelligent PID control method using Neural Network (NN) combined with type Particle Swarm Optimization (PSO) is developed. In the method, the intelligent controller is designed based on variable gain type PID control using NN. The learning of the NN unit is implemented by the PSO. The PID gains are adjusted by the intelligent controller in real-time environment. The effectiveness of the method is confirmed by experiments.
Keywords :
control system synthesis; machine control; neurocontrollers; particle swarm optimisation; three-term control; ultrasonic motors; MRI environment; NN unit learning; PID gains; PSO-type NN; USM; actuators; intelligent PID control; intelligent controller design; medical area; neural network; particle swarm optimization; real-time environment; ultrasonic motors; variable gain-typed PID control; welfare area; Artificial neural networks; Forecasting; Robot sensing systems; Servosystems; Sun;
Conference_Titel :
Consumer Electronics (GCCE), 2014 IEEE 3rd Global Conference on
Conference_Location :
Tokyo
DOI :
10.1109/GCCE.2014.7031179