عنوان	Self-adaptive RBF neural network PID controller in linear elevator
نوع پژوهش	مقاله ارائه شده کنفرانسی
کلیدواژه‌ها	Elevators, Permanent magnets, Synchronous motors, Mathematical model, Control systems, Artificial neural networks, Vectors
چکیده	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.
پژوهشگران	محمد باقر بنا شریفیان (نفر اول)، احد میرلو (نفر دوم)، جعفر طاووسی (نفر سوم)، مهران صباحی (نفر چهارم)