Speed response of brushless DC motor using fuzzy PID controller under varying load condition

ABSTRACT

The increasing trend towards usage of precisely controlled, high torque, efficient and low noise motors for dedicated applications has attracted the at tention of researcher in Brushless DC (BLDC) motors. BLDC motors can act as an acceptable alternative to the conventional motors like Induction Motors, Switched Reluctance Motors etc. This paper presents a detailed study on the performance of a BLDC motor supplying different types of loads, and at the same time, deploying different control techniques. An advance Fuzzy PID controller is compared with the commonly used PID controller. The load variations considered are of the most common types, generally encountered in practice. A comparison has been carried out in this paper by observing the dynamic speed response of motor at the time of application as well as at the time of removal of the load. The BLDC motors suffer from a major drawback of having jerky behavior at the time of load removal. The study reveals that irrespective of the type of controller used, the gradual load variation produces better results as against sudden load variations. It is further observed that in addition to other dynamic features, the jerks produced at the time of load removal also get improved to a large extent with Fuzzy PID controller. The speed torque characteristics un raveled the fact that the jerks are minimum at the time of gradual load removal with Fuzzy PID controller in place. An attempt has been made to define these jerks by ‘Perturbation Window’.

KEYWORDS:

  1. BLDC motor
  2. Proportional-integral-derivative (PID) controller
  3. Fuzzy (FL) controller
  4. MATLAB/SIMULINK

 SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:


 Fig.1.Block diagram of BLDC motor drive.

  EXPERIMENTAL RESULTS:

Fig.2.(a) Speed response curve (b) current response curve (c) torque response curve with PID controller under gradual application and removal of load.

Fig.3.(a) Speed response curve (b) current response curve (c) torque response curve with Fuzzy PID controller under sudden application and removal of load.

Fig.4.(a) Speed response curve (b) current response curve (c) torque response curve with Fuzzy PID controller. under sudden application and removal of load

Fig.5.(a) Speed response curve (b) current response curve (c) torque response curve with Fuzzy PID controller under sudden application and removal of load.

Fig.6.(a) Speed response curve (b) current response curve (c) torque response curve with Fuzzy PID controller under gradual application and removal of load.

CONCLUSION

A model is developed in this paper for BLDC Drive using MATLAB/SIMULINK to analyze its performance with PID controller and with Fuzzy PID Controller when the motor is subjected to the most commonly encountered sudden load variations as well as gradual load variations under constant speed operation. The BLDC drive gives better performance if the load is changed gradually. Further, it is found that the transient response of the drive in terms of overshoot, under shoot, peak time and settling time are improved with the use of FPID. Speed torque characteristics of The drive are also used for all the conditions to assess the overall behavior of the machine. The commonly experienced major drawback of the jerks of BLDC motors at the time of load removal has been found to get reduced by 50% incase of sudden load removal and by about 80% incase of gradual load removal by applying FPID controller as against the use of classical PID controller.

REFERENCES

Arulmozhiyal, R., Kandiban, R., 2012. Design of Fuzzy PID controller for Brushless DC motor. In: International conference on Computer Communication and Informatics (ICCCI—2012), Jan.10–12, Coimbatore, INDIA.

Baldursson,S.,2005. BLDC Motor Modelling and Control—A MATLAB/Simulink Implementation, Master Thesis.

Dorf,C.,Richard,C.,Robert Bishop,H.,2001.Modern control systems,9thed.Prentice Hall Inc.,New Jersey-07458,USA,Chapters 1,5,pp.1–23,pp.173–206.

Farouk,Naeim,Bingqi,Tian,2012.Application of self-tuning Fuzzy PID controller on the AVR system. In: IEEE Conference of Mechatronics and Automation,August5–8,Chengdu,China.

Gupta,D.,2016.Speed control of Brushless DC motor using Fuzzy PID controller.11–12 March KNIT, IndiaIn: IEEE conference on Emerging trends in Electrical, Electronics & Sustainable Energy System,Volume2,pp.221–224.

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.

A Comparative Study on the Speed Response of BLDC Motor Using Conventional PI Controller, Anti-windup PI Controller and Fuzzy Controller

A Comparative Study on the Speed Response of BLDC Motor Using Conventional PI Controller, Anti-windup PI Controller and Fuzzy Controller

ABSTRACT:

Brushless dc motors (BLDC) are widely used for various applications because of high torque, high speed and smaller size. This type of motors are non linear in nature and are affected highly by the non-linearities like load disturbance. Speed control of this motor is traditionally handled by conventional PI and PID controllers. This paper presents the speed control of BLDC motor using anti wind up PI controller. Problems like rollover can arise in conventional PI controller due to saturation effect. In order to avoid such problems anti wind up schemes are introduced. As the fuzzy controller has the ability to control and as it is simple to calculate, a fuzzy controller is also designed for speed control of BLDC motor. The control and simulation of BLDC motor have been done using software MATLAB/SIMULINK. The simulation results using anti wind up PI controller and fuzzy controller are compared with PI controller.

KEYWORDS:

  1. BLDC
  2. Speed response
  3. PI controller
  4. Fuzzy
  5. Anti windup

 

SOFTWARE: MATLAB/SIMULINK

 

BLOCK DIAGRAM:

 

Fig.1. Simulation block diagram

  

EXPECTED SIMULATION RESULTS:

  

Fig.2. Speed response under no load

Fig.3. Speed response for step increase in speed

Fig.4. Speed response for step increase in speed

Fig.5. Speed response under loaded condition

Fig.6.Speed response under load condition

 

CONCLUSION:

 This paper presents the speed control of BLDC motor using anti wind up PI controller and fuzzy controller for three phase BLDC motor. The simulation results are compared with PI controller results. The conventional PI controller results are slower compared to fuzzy and anti wind up controllers. From the simulation results, it is clear that for the load variation anti wind up PI controller gave better response than conventional PI and fuzzy controller. Hence anti wind up PI controller is found to be more suitable for BLDC motor drive during load variation. It can also be observed from the simulation results that performance of fuzzy controller is better during the case of speed variation.

 

REFERENCES:

[1] R. Arulmozhiyal, R. Kandibanv, “Design of Fuzzy PID Controller for Brushless DC Motor”, in Proc. IEEE International Conference on Computer Communication and Informatics, Coimbatore, 2012.

[2] Anirban Ghoshal and Vinod John, “Anti-windup Schemes for Proportional Integral and Proportional Resonant Controller”, in Proc. National Power electronic conference, Roorkee, 2010.

[3] M. F. Z. Abidin, D. Ishak and A. Hasni Abu Hassan, “A Comparative Study of PI, Fuzzy and Hybrid PI Fuzzy Controller for Speed Control of Brushless DC Motor Drive”, in Proc. IEEE International conference on Computer applications and and Industrial electronics, Malysia, 2011.

[4] J. Choi, C. W Park, S. Rhyu and H. Sung, “Development and Control of BLDC Motor using Fuzzy Models”,in Proc. IEEE international Conference on Robotics, Automation and Mechatronics, Chengdu, 2004.

[5] C. Bohn and D.P. Atherton, “An analysis package comparing PID anti-windup strategies,” IEEE Trans. controls system, Vol.15, No. 2, pp.34-40, 1995.