Title :
Self-adaptive RBF neural network PID controller in linear elevator
Author :
Sharifian, M.B.B. ; Mirlo, A. ; Tavoosi, J. ; Sabahi, M.
Author_Institution :
Fac. of Electr. & Comput. Eng., Univ. of Tabriz, Tabriz, Iran
Abstract :
In this paper self adaptive RBF neutral network PID controller for linear elevator is presented. RBFNN is widely used in many fields to solve computational problems that are difficult to solve by conventional method. Nowadays with the rapid development of permanent magnet linear synchronous motor (PMLSM) application in elevators, the design of PID controllers of these systems are very important. This paper, analyzed the control requirements of Linear Elevator system, combined control characteristics of neural network and PID based on mathematical model of PMLSM, a control system of PMLSM for hoisting system are designed. The PMLSM model has been developed in MATLAB/Simulink and the RBFNN has been applied to online tuning PID controller. The results show the good performance of this method. The results of simulation showed that the control system with external disturbance and Parameter change is effective.
Keywords :
adaptive control; control system synthesis; lifts; linear synchronous motors; machine control; neurocontrollers; permanent magnet motors; radial basis function networks; three-term control; MATLAB-Simulink; PID controller design; RBF neutral network controller; hoisting system; linear elevator system; mathematical model; online tuning controller; parameter change; permanent magnet linear synchronous motor application; self adaptive controller; Artificial neural networks; Control systems; Elevators; Mathematical model; Permanent magnets; Synchronous motors; Vectors; Linear Elevator; PID; PMLSM; RBF Neural Network;
Conference_Titel :
Electrical Machines and Systems (ICEMS), 2011 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4577-1044-5
DOI :
10.1109/ICEMS.2011.6073387
