Adaptive Speed Control of Brushless DC (BLDC) Motor Based on Interval Type-2 Fuzzy Logic

 

ABSTRACT:

To precisely control the speed of BLDC motors at high speed and with very good performance, an accurate motor model is required. As a result, the controller design can play an important role in the effectiveness of the system. The classic controllers such as PID are widely used in the BLDC motor controllers, but they are not appropriate due to non-linear model of the BLDC motor. To enhance the performance and speed of response, many studies were taken to improve the adjusting methods of PID controller gains by using fuzzy logic. Use of fuzzy logic considering approximately interpretation of the observations and determination of the approximate commands, provides a good platform for designing intelligent robust controller. Nowadays type-2 fuzzy logic is used because of more ability to model and reduce uncertainty effects in rule-based fuzzy systems. In this paper, an interval type-2 fuzzy logic-based proportional-integral-derivative controller (IT2FLPIDC) is proposed for speed control of brushless DC (BLDC) motor. The proposed controller performance is compared with the conventional PID and type-1 fuzzy logic-based PID controllers, respectively in MATLAB/Simulink environment. Simulation results show the superior IT2FLPIDC performance than two other ones.

KEYWORDS:

  1. Brushless DC (BLDC) Motor
  2. Invertal Type-2 Fuzzy Logic
  3. Speed Control
  4. Self-tuning PID Controller

  SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Figure 1. Block Diagram of speed control of BLDC Motor

EXPECTED SIMULATION RESULTS:

Figure 2. Speed Deviation of BLDC Motor

Figure 3. Load Deviation of BLDC Motor

Figure 4. Torque Deviation of BLDC Motor

 CONCLUSION:

In this paper, the speed control of the BLDC motor is studied and simulated in MATLAB/Simulink. In order to overcome uncertainties and variant working condition, the adjustment of PID gains through fuzzy logic is proposed. In this study, three controller types are considered and compared: conventional PID, type-1 and type-2 fuzzy-based self-tuning PID controllers. The simulation results show that type-2 fuzzy PID controller has superior performance and response than two other ones.

REFERENCES:

[1] A. Sathyan, N. Milivojevic, Y. J. Lee, M. Krishnamurthy, and A. Emadi, “An FPGA-based novel digital PWM control scheme for BLDC motor drives,” IEEE Trans. Ind. Electron., vol. 56, no. 8, pp. 3040–3049,Aug. 2009.

[2] F. Rodriguez and A. Emadi, “A novel digital control technique for brushless DC motor drives,” IEEE Trans. Ind. Electron., vol. 54, no. 5, pp. 2365–2373, Oct. 2007.

[3] Y. Liu, Z. Q. Zhu, and D. HoweDirect Torque Control of Brushless DC Drives With Reduced Torque RippleIEEE Trans. Ind. Appl., vol. 41, no. 2, pp. 599-608, March/April 2005.

[4] T. S. Kim, S. C. Ahn, and D. S. Hyun , “A New Current Control Algorithm for Torque Ripple Reduction of BLDC Motors,” in IECON’01, 27th Conf. IEEE Ind. Electron Society,2001

[5] W. A. Salah, D. Ishak, K. J. Hammadi, “PWM Switching Strategy for Torque Ripple Minimization in BLDC MotorFEI STU, Journal of Electrical Engineering, vol. 62, no. 3, 2011, 141–146.

Single Stage Solar PV Fed Brushless DC Motor Driven Water Pump

 

ABSTRACT:

In order to optimize the solar photovoltaic (PV) generated power using a maximum power point tracking (MPPT) technique, a DC-DC conversion stage is usually required in solar PV fed water pumping which is driven by a brushless DC (BLDC) motor. This power conversion stage leads to an increased cost, size, complexity and reduced efficiency. As a unique solution, this work addresses a single stage solar PV energy conversion system feeding a BLDC motor-pump, which eliminates the DC-DC conversion stage. A simple control technique capable of operating the solar PV array at its peak power using a common voltage source inverter (VSI), is proposed for BLDC motor control. The proposed control eliminates the BLDC motor phase current sensors. No supplementary control is associated for the speed control of motor-pump and its soft start. The speed is controlled through the optimum power of solar PV array. The suitability of proposed system is manifested through its performance evaluation using MATLAB/Simulink based simulated results and experimental validation on a developed prototype, under the practical operating conditions.

KEYWORDS:

  1. MPPT
  2. Solar PV array
  3. BLDC motor
  4. Water pump
  5. VSI
  6. Soft starting
  7. Speed control

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

 

Fig.1 Proposed water pumping based on a single stage solar PV energy conversion system.

EXPECTED SIMULATION RESULTS:

 Fig.2 Steady state and starting performance of (a) PV array and (b) motor pump, of proposed system at 1 kW/m2.

Fig.3 Steady state and starting response of (a) PV array and (b) motor-pump, of proposed system at 200 W/m2.

Fig.4 Dynamic performance of (a) PV array and (b) BLDC motor Pump ,of Proposed  water pumping system.

Fig. 5 Responses of (a) PV array and (b) BLDC motor, under partial shading

CONCLUSION:

The proposed BLDC motor driven water pumping based on a single stage solar PV generation has been validated through a demonstration of its various steady state, starting and dynamic performances. The system has been simulated using the MATLAB toolboxes, and implemented on an experimental prototype. The topology of the proposed system has provided a DC-DC converter-less solution for PV fed brushless DC motor driven water pumping. Moreover, the motor phase current sensing elements have been eliminated, resulting in a simple and cost-effective drive. The other desired functions are the speed control without any additional circuit and a soft start of the motor-pump. A detailed comparative analysis of the proposed and the existing topologies has ultimately manifested the superiority of the proposed work.

REFERENCES:

[1] C. Jain and B. Singh, “An Adjustable DC Link Voltage Based Control of Multifunctional Grid Interfaced Solar PV System,” IEEE J. Emerg. Sel. Topics Power Electron., Early Access.

[2] A. A. A. Radwan and Y. A. R. I. Mohamed, “Power Synchronization Control for Grid-Connected Current-Source Inverter-Based Photovoltaic Systems,” IEEE Trans. Energy Convers., vol. 31, no. 3, pp. 1023-1036, Sept. 2016.

[3] P. Vithayasrichareon, G. Mills and I. F. MacGill, “Impact of Electric Vehicles and Solar PV on Future Generation Portfolio Investment,” IEEE Trans. Sustain. Energy, vol. 6, no. 3, pp. 899-908, July 2015.

[4] A. K. Mishra and B. Singh, “A single stage solar PV array based water pumping system using SRM drive,” IEEE Ind. Appl. Soc. Annu. Meeting, Portland, OR, 2016, pp. 1-8.

[5] S. Jain, A.K. Thopukara, R. Karampuri and V.T. Somasekhar, “A Single-Stage Photovoltaic System for a Dual-Inverter-Fed Open-End Winding Induction Motor Drive for Pumping Applications,” IEEE Trans. Power Electron., vol. 30, no. 9, pp. 4809 – 4818, Sept. 2015.

A Comparative Study of PI, Fuzzy and Hybrid PI Fuzzy Controller for Speed Control of Brushless DC Motor Drive

ABSTRACT: 

This paper presents the comparative study between PI, fuzzy and hybrid PI-Fuzzy controller for speed control of brushless dc (BLDC) motor. The control structure of the proposed drive system is described. The simulation results of the drive system for different operation modes are evaluated and compared. A fuzzy controller offers better speed response for start-up while PI controller has good compliance over variation of load torque but has slow settling response. Hybrid controller has an advantage of integrating a superiority of these two controllers for better control performances. Matlab/Simulink is used to carry out the simulation.

KEYWORDS:
1. PI
2. Fuzzy
3. Hybrid Controller
4. BLDC Motor
5. Speed Control

SOFTWARE: MATLAB/SIMULINK

SIMULINK DIAGRAM:

Figure 1: Simulation model BLDC motor drive

EXPECTED SIMULATION RESULTS:

Figure 2: PI controller

Figure 3: Fuzzy controller

Figure 4: Hybrid controller

Figure 5: Comparison of speed response

Figure 6: PI controller

Figure 7: Fuzzy controller

Figure 8: Hybrid controller

Figure 9: Comparison of speed response

CONCLUSION:
From simulation results, it was shown that PI controller maintained the steady state accuracy while the fuzzy controller performed well in the case of sufficiently large reference input changes with shorter settling time. The hybrid controller has integrated both fuzzy controller and PI controller. During the large speed error, the fuzzy controller will be selected by switch. When the speed error is less than 0.28 rpm, the PI controller will be selected to maintain the high steady-state accuracy. The simulation results showed that the hybrid controller has incorporated advantage of both fuzzy and PI controller. As a conclusion, the hybrid controller has improved the dynamic performance of BLDC motor.
REFERENCES:
[1] F. Farkas, A. Zakharov and S.Z. Varga, “Speed and position controller for dc drives using fuzzy logic”, Studies in Applied Electromagnetics and Mechanics (Vol. 16): Applied Electromagnetics and Computational Technology II, Amsterdam: IOS Press, 2000.
[2] Zulkifilie Ibrahim and Emil Levi, “A comparative analysis of fuzzy logic and pi speed control in high-performance ac drives using experimental approach”, IEEE Trans. on Industry Applications 38(5): pg 1210-1218, 2002.
[3] L.S. Xuefang, F. Morel, A.M. Llor, B. Allard, J.-M. Retif, “Implementation of hybrid control for motor drives”, IEEE Trans. Industrial Electronics, vol.38, No. 5, pp. 1210-1218, Sep. 2002.
[4] Krishnan R, Permanent magnet synchronous and brushless DC motor drives, Boca Raton: CRC Press, 2010
[5] Lini Mathew and Vivek Kumar Pandey, “Design and deelopment of fuzzy logic controller to control the speed of permanent magnet synchronous motor”, JEEER, vol. 3(3), pp. 52-61, March 2011.

Solar PV Array Fed Brushless DC Motor Driven Water Pump

 

ABSTRACT:

 This work deals with the utilization of solar photovoltaic (SPV) energy in the brushless DC (BLDC) motor driven water pump. A DC-DC boost converter, used as an intermediate power conditioning unit plays a vital role in efficiency enhancement of SPV array and soft starting of the BLDC motor with proper control. The speed control of BLDC motor is performed by PWM (Pulse Width Modulation) control of the voltage source inverter (VSI) using DC link voltage regulator. No additional control or current sensing element is required for speed control. The behavior of proposed pumping system is demonstrated by evaluating its various performances through MATLAB/simulink based simulation study.

KEYWORDS:

  1. Solar PV
  2. BLDC motor
  3. Boost converter
  4. Soft starting
  5. PWM
  6. VSI
  7. Speed control

 SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig.1 Configuration of PV array fed BLDC motor-pump.

 EXPECTED SIMULATION RESULTS:

 

Fig.2 Starting and steady state performances of solar PV array

Fig.3 Starting and steady state performance of boost DC-DC converter

Fig.4 Starting and steady state performance of brushless DC motor-pump

Fig.5 Dynamic performance of solar PV array.

Fig.6 Dynamic performance of boost DC-DC converter

Fig.7 Dynamic performance of brushless DC motor – pump

CONCLUSION:

The SPV Array fed boost converter based BLDC motor driven water pump has been proposed and its suitability has been demonstrated by analyzing its various performance indices using MATLAB based simulation study. A simple, efficient and economical method for speed control of BLDC motor has been suggested, which has offered absolute elimination of current sensing elements. The proper selection of SPV array has made the boost converter capable of tracking MPP irrespective of weather conditions. An optimum design of the boost converter has been presented. The safe starting of brushless DC motor has been achieved without any additional control. The desired performance of proposed system even at 20% of standard solar irradiance has justified its suitability for solar PV based water pumping.

REFERENCES:

[1] R. Kumar and B. Singh, “Solar PV array fed Cuk converter-VSI controlled BLDC motor drive for water pumping,” 6th IEEE Power India Int. Conf. (PIICON), 5-7 Dec. 2014, pp. 1-7.

[2] M. A. Elgendy, B. Zahawi and D. J. Atkinson, “Assessment of the Incremental Conductance Maximum Power Point Tracking Algorithm,” IEEE Trans. Sustain. Energy, vol.4, no.1, pp.108-117, Jan. 2013.

[3] J.V. Mapurunga Caracas, G. De Carvalho Farias, L.F. Moreira Teixeira and L.A. De Souza Ribeiro, “Implementation of a High-Efficiency, High-Lifetime, and Low-Cost Converter for an Autonomous Photovoltaic Water Pumping System,” IEEE Trans. Ind. Appl., vol. 50, no. 1, pp. 631-641, Jan.-Feb. 2014.

[4] N. Mohan, T. M. Undeland and W. P. Robbins, Power Electronics: Converters, Applications and Design, 3rd ed. New Delhi, India: John Wiley & Sons Inc., 2010.

[5] M. H. Rashid, Power Electronics Handbook: Devices, Circuits, and Applications,” 3rd ed. Oxford, UK: Elsevier Inc., 2011.

 

Indirect Vector Control of Induction Motor Using Sliding-Mode Controller

 

ABSTRACT:

The paper presents a sliding-mode speed control system for an indirect vector controlled induction motor drive for high performance. The analysis, design and simulation of the sliding-mode controller for indirect vector control induction motor are carried out. The proposed sliding-mode controller is compared with PI controller with no load and various load condition. The result demonstrates the robustness and effectiveness of the proposed sliding-mode control for high performance of induction motor drive system.

 KEYWORDS:

  1. Indirect vector control
  2. Sliding mode control
  3. PI controller
  4. Induction motor
  5. Speed control

 SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

image001

Figure 1: Indirect vector controlled induction motor drive

EXPECTED SIMULATION RESULTS:

 image002

Figure 2: Speed response of PI controller at no load

image003

Figure 3:Speed response of Sliding-mode controller at no load

image004

Figure 4: Speed response of PI controller at load

image005

Figure 5: Speed response of Sliding- mode controller at load

image006

Figure 6:X-Y plot of Rotor flux of PI controller

image007

Figure 7: x-v plot of Rotor flux of Sliding-mode controller

CONCLUSION:

In this paper sliding-mode controller for the control of an indirect vector-controlled induction motor was described. The drive system was simulated with sliding-mode controller and PI controller and their performance was compared. Here simulation results shows that the designed sliding-mode controller realises a good dynamic behaviour of the motor with a rapid settling time, no overshoot and has better performance than PI controller. Sliding-mode control has more robust during change in load condition.

.REFERENCES:

[1] B.K Bose “Modern power electronics and ac drives “Prentice-Hall OJ India, New Delhi, 2008.

[2] M.Masiala;B.Vafakhah,;A.Knght,;J.Salmon,;”Performa nce of PI and fuzzy logic speed control of field-oriented induction motor drive,” CCECE , jul. 2007, pp. 397-400.

[3] F.Barrero;A.Gonzalez;A.Torralba,E.Galvan,;L.G.Franqu elo; “Speed control of induction motors using a novel Fuzzy-sliding mode structure,”IEEE Transaction on Fuzzy system, vol. 10, no.3, pp. 375-383, Jun 2002.

[4] H.F.Ho,K.W.E.Cheng, “position control of induction motor using indirect adaptive fuzzy sliding mode control,” P ESA, , Sep. 2009, pp. 1-5.

[5] RKumar,R.A.Gupta,S.V.Bhangale, “indirect vector controlled induction motor drive with fuzzy logic based intelligent controller,” IETECH Journals of Electrical Analysis, vol. 2, no. 4, pp. 211-216, 2008.

 

 

 

Speed Control of PMBLDC Motor Using MATLAB/Simulink and Effects of Load and Inertia Changes

ABSTRACT:

Modeling and simulation of electromechanical systems with machine drives are essential steps at the design stage of such systems. This paper describes the procedure of deriving a model for the brush less dc motor with 120-degree inverter system and its validation in the MATLAB/Simulink platform. The discussion arrives at a closed-loop speed control, in which PI algorithm is adopted and the position-pulse determination is done through current control for a standard trapezoidal BLDC motors. The simulation results for BLDC motor drive systems confirm the validity of the proposed method.

 KEYWORDS:

  1. PMBLDC Motor
  2. Simulation and modeling
  3. Speed control

 SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

 image001

Figure 1. PMBLDC motor drive system

EXPECTED SIMULATION RESULTS:

Steady state currentimage002

Figure 2. Stator phase currents

Back EMF of the BLDC motor

image003

Figure 3. Trapezoidal back EMF

image004

Figure 4. Reference current waveform

image005

Figure 5. Representative phase voltage (van)

image006

Figure 6. Torque and speed responses during startup transients

image007

Figure 7. Torque and speed responses – step input change – moment of inertia 0.013 kg-m2 (step time 0.5 S)

image008

Figure 8 Torque and speed responses at moment of inertia 0.098 kg-m’

image009

Figure 9. Torque and speed-Step input with moment of inertia 0.098

kg-m2 (step time 0.5 S)

image010

Figure 10. Step load torque (9Nm) at 0.75 step

image011

Figure 11. Step load torque (25 Nm) at 0.75

image012

Figure 12. Application of heavy load (100 Nm)

image013

Figure 13. Load toque 25Nm at step of 0.5

CONCLUSION:

The nonlinear simulation model of the BLDC motors drive system with PI control based on MATLAB/Simulink platform is presented. The control structure has an inner current closed-loop and an outer-speed loop to govern the current. The speed controller regulates the rotor movement by varying the frequency of the pulse based on signal feedback from the Hall sensors. The performance of the developed PI algorithm based speed controller of the drive has revealed that the algorithm devises the behavior of the PMBLDC motor drive system work satisfactorily. Current is regulated within band by the hysteresis current regulator. And also by varying the moment of inertia observe that increase in moment of inertia it increases simulation time to reach the steady state value. Consequently, the developed controller has robust speed characteristics against parameters and inertia variations. Therefore, it can be adapted speed control for high performance BLDC motor.

REFERENCES:

[I] Duane C.Hanselman, “Brushless Permanent-Magnet Motor Design”, McGraw-Hill, Inc., New York, 1994.

[2] TJ.E. Miller, ‘Brushless Permanent Magnet and Reluctance Motor Drives.’ Oxford Science Publication, UK, 1989.

[3] RKrishnan, Electric Motor Drives: Modeling, Analysis, and Control, Prentice-Hall, Upper Saddle River, NJ, 2001.

[4] P Pillay and R Krishnan, “Modeling, simulation, and analysis of permanent Magnet motor drives. Part II: The brushless dc motor drive,” IEEE Transactions on Industry Applications, vol.IA-25, no.2, pp.274-279, Mar./Apr. 1989.

[5] RKrishnan and A. J. Beutler, “Performance and design of an axial field permanent magnet synchronous motor servo drive,” Proceedings of IEEE lASAnnual Meeting, pp.634-640,1985.