The Control brushless DC motor of speed and position with fuzzy neuro controller

BrusMess DC Motor (BLDCM) has been used widely in the industrial applications which were required sensitive speed and position. In these type industrial applications, BLDCM must not be affected by the nonlinear and unknown motor dynamics with motor parameters and load changes. BLDCM with adaptive structure have effective control formation in sensitive speed and position control of the systems which are nonlinear and variable with the time, in compare to conventional controller. In many works which have been accomplished on speed and position control of BLDCM with various Fuzzy Neuro Controller (FNC), they have been known that motor has been affected by load changes and thus, steady state error has been found in the motor speed and position. In addition, in many of these works, elected membership functions for input variable were in same type and different membership functions were not used for FNC. In this thesis, FNC were purposed to use speed/position error with speed/position error alteration to be input variation and to gain integral feature to its existence for sensitive speed and position control of BLDCM with vectorIV in motor controller to prove the performance of purposed controller. In the simulation and experimental results, FNC which have been designed for sensitive speed and position control of BLDCM were more effective and quick in compare to other controller. The simulation and training works of controller were accomplished to be quantitative with MATLAB/SIMULINK program and DSPACE 1104 controller card with respect to. Science Code : 626.01.01 Key Words : Brushless DC motor, Fuzzy Logic, Artificial neural network, Fuzzy neuro controller, DS1104 Digital signal processor Page Number : 157 Adviser : Prof. Dr. Ismail COŞKUN