Control of BLDC Motor Based on Adaptive Fuzzy Logic PID Controller

ABSTRACT: 

This paper presents an Adaptive fuzzy logic PID controller for speed control of Brushless Direct current Motor drives which is widely used in various industrial systems, such as servo motor drives, medical, automobile and aerospace industry. BLDC motors were electronically commutated motor offer many advantages over Brushed DC Motor which includes increased efficiency, longer life, low volume and high torque. This paper presents an overview of performance of fuzzy PID controller and Adaptive fuzzy PID controller using Simulink model. Tuning Parameters and computing using Normal PID controller is difficult and also it does not give satisfied control characteristics when compare to Adaptive Fuzzy PID controller. From the Simulation results we verify that Adaptive Fuzzy PID controller give better control performance when compared to fuzzy PID controller. The software Package SIMULINK was used in control and Modelling of BLDC Motor.

KEYWORDS: 

1. Brushless DC motors (BLDCM)
2. Fuzzy PID controller
3. Adaptive Fuzzy PID controller

SOFTWARE: MATLAB/SIMULINK


BLOCK DIAGRAM:

 Fig.1. Speed control of BLDC motor

EXPECTED SIMULATION RESULTS: 

Fig.2. Speed characteristics with no load speed of 3000 rpm

Fig.3. Torque characteristics with no load speed of 3000 rpm

Fig. 4. Speed characteristics with no load step down speed of 3000- 2500 rpm

Fig.5. Torque characteristics with no load step down speed of 3000-2500 rpm

Fig.6. Speed characteristics with load speed of 3000 rpm

Fig.7. Torque characteristics with load speed of 3000 rpm

                                                                                                                                                                     CONCLUSION:

This paper presents the performance of fuzzy PID controller and Adaptive Fuzzy PID controller of BLDC motor for speed control using Simulink model. Combination of fuzzy control and conventional PID controller establishes an intelligent control, which regulates the control parameters depending upon the error. Two inputs and three outputs were used in this fuzzy adaptive PID controller. From the Simulation, BLDC motor speed control of Adaptive fuzzy PID controller had better performance than fuzzy PID controller for the same operation condition, mainly when BLDC motor operates in different speed and also BLDC motor speed to be constant when the load varies. Simulation results were also shows that fuzzy logic adaptive PID controller had lesser overshoot, faster response and better stability.

REFERENCES:

[1] Anjali.A.R “Control Of Three Phase BLDC Motor Using Fuzzy Logic Controller” International Journal of Engineering Research & Technology (IJERT), Vol. 2, Issue 7, July 2013.

[2] R. Kandiban, R. Arulmozhiyal “Design of Adaptive Fuzzy PID Controller for Speed control of BLDC Motor” International Journal of Soft Computing and Engineering ,Volume-2, Issue-1, March 2012.

[3] Uzair Ansari, Saqib Alam, Syed Minhaj un Nabi Jafri, “Modelling and Control of Three Phase BLDC Motor using PID with Genetic Algorithm”, UK Sim 13th International Conference on Modelling and Simulation,pp.189-194,2011

[4] R.Arulmozhiyal and K.Baskaran, “Implementation of Fuzzy PI Controller for Speed Control of Induction Motor Using FPGA”, Journal of Power Electronics, Vol.10, No.1, pp.65-71, Jan 2010.

[5] Vinod Kr Singh Patel, A.K.Pandey, “Modelling and Simulation of Brushless DC Motor Using PWM Control Technique”, International Journal of Engineering Research and Applications, Vol. 3, Issue 3, May-Jun 2013, pp.612-620.