A Comparative Study of Speed Control of D.C. Brushless Motor Using PI and Fuzzy Controller

ABSTRACT: 

This paper presents an intelligent control architecture for a sensor based brushless DC motor. A BLDC motor is superior to a brushed DC motor, as it replaces the mechanical commutation unit with an electronic one; hence improving the dynamic characteristics, efficiency and reducing the noise level marginally. Conventionally a PI-controller is used for speed control purpose in many industrial BLDC motor drives. But the accuracy level obtained by the PI-controlled drive is insufficient for advanced sophisticated applications. So as a better choice, a fuzzy logic control technique is applied to this motor to achieve a greater accuracy in controlling the speed.

KEYWORDS: 
1. Intelligent control
2. BLDC motor
3. Dynamic characteristics
4. Accuracy
5. Fuzzy logic

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAMS:

Fig. 1. Block diagram for speed control of BLDCM using PI controller.

Fig. 2. Block diagram of a fuzzy logic controlled BLDC motor drive.

EXPECTED SIMULATION RESULTS: 

                 

Fig. 3. Speed response of PI controlled BLDC motor drive(Nref=1500 r.p.m)

Fig. 4. Speed response of fuzzy logic controlled BLDC motor drive (Nref=1500 r.p.m)

Fig. 5. Speed response of PI controlled BLDC motor drive(transition from 1500 r.p.m to 1400 r.p.m)

Fig. 6. Speed response of fuzzy logic controlled BLDC motor drive (transition from 1500 r.p.m to 1400 r.p.m)

                                                                                                                                                                     CONCLUSION:

In this paper we discussed the BLDC motor speed control using a fuzzy logic controller. A detailed analysis was done on fuzzification, fuzzy rules and defuzzification methods and lookup table was obtained by using fuzzy algorithm. The PI control scheme and fuzzy based PI scheme were simulated using MATLAB and compared. The dynamic response of speed in using FLC was better than only PI scheme. These results show that a PI based FLC technique is a better choice for BLDC motor drive and favors to widen its area of application in near future.

REFERENCES:

[1] Paul C. Krause, "Analysis of electric machinary", McGraw-Hill, 1984.

[2] P.S. Bimbhra, “ Generalized Theory of Electrical Machines”, Khanna Publishers.

[3] P. Yedamale, Brushless DC (BLDC) Motor Fundamentals. Application Note 885, Microchip Technology Inc., Chandler, AZ,2003.

[4] Dutta, P.; Mahato, S.N., "Design of mathematical model and performance analysis of BLBLDC motor," Control, Instrumentation, Energy and Communication (CIEC), 2014 International Conference on , vol., no., pp.457,461, Jan. 31 2014-Feb. 2 2014

[5] Ko, J.S.; Jae Gyu Hwang; Myung-Joong Youn, "Robust position control of BLDD motors using integral-proportional plus fuzzy logic controller," Industrial Electronics, Control, and Instrumentation, 1993. Proceedings of the IECON '93., International Conference on , vol., no., pp.213,218 vol.1, 15-19 Nov 1993

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.

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.

Design and Implementation of a Novel Multilevel DC–AC Inverter

 ABSTRACT:

 In this paper, a novel multilevel dc–ac inverter is proposed. The proposed multilevel inverter generates seven-level ac output voltage with the appropriate gate signals’ design. Also, the low-pass filter is used to reduce the total harmonic distortion of the sinusoidal output voltage. The switching losses and the voltage stress of power devices can be reduced in the proposed multilevel inverter. The operating principles of the proposed inverter and the voltage balancing method of input capacitors are discussed. Finally, a laboratory prototype multilevel inverter with 400-V input voltage and output 220 Vrms/2 kW is implemented. The multilevel inverter is controlled with sinusoidal pulse-width modulation (SPWM) by TMS320LF2407 digital signal processor (DSP). Experimental results show that the maximum efficiency is 96.9% and the full load efficiency is 94.6%.

KEYWORDS:

1.      DC–AC inverter

2.      Digital signal processor (DSP)

3.      Maximum power point tracking (MPPT)

4.      Multilevel

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig. 1. Block diagram of renewable system.

EXPECTED SIMULATION RESULTS:

Fig. 2. Waveforms of v_gs1, v_ab, v_o, and i_o at 500 W.

Fig. 3. Output voltage harmonic spectrum of v_ab calculated by FFT.

Fig. 4. Output voltage harmonic spectrum of v_o calculated by FFT

Fig. 5. Waveforms of vC2, v_o, and i_o at 1000 W.

Fig. 6. Waveforms of vC2, v_o, and i_o at 2000 W.

Fig. 7. Waveforms of v_o and i_o at 400 VA.

CONCLUSION:

A novel seven-level inverter was designed and implemented with DSP in this paper. The main idea of the proposed configuration is to reduce the number of power device. The reduction of power device is proved by comparing with traditional structures. Finally, a laboratory prototype of seven-level inverter with 400-V input voltage and output 220 Vrms/2kW is implemented. Experimental results show that the maximum efficiency is 96.9% and the full load efficiency is 94.6%.

REFERENCES:

[1] R. Gonzalez, E. Gubia, J. Lopez, and L. Marroyo, “Transformerless single-phase multilevel-based photovoltaic inverter,” IEEE Trans. Ind. Electron., vol. 55, no. 7, pp. 2694–2702, Jul. 2008.

[2] S. Daher, J. Schmid, and F. L.M. Antunes, “Multilevel inverter topologies for stand-alone PV systems,” IEEE Trans. Ind. Electron., vol. 55, no. 7, pp. 2703–2712, Jul. 2008.

[3] W. Yu, J. S. Lai, H. Qian, and C. Hutchens, “High-efficiency MOSFET inverter with H6-type configuration for photovoltaic nonisolated, acmodule applications,” IEEE Trans. Power Electron., vol. 26, no. 4, pp. 1253–1260, Apr. 2011.

[4] R. A. Ahmed, S. Mekhilef, and W. P. Hew, “New multilevel inverter topology with minimum number of switches,” in Proc. IEEE Region 10 Conf. (TENCON), 2010, pp. 1862–1867.

[5] M. R. Banaei and E. Salary, “New multilevel inverter with reduction of switches and gate driver,” in Proc. IEEE 18th Iran. Conf. Elect. Eng. (IECC), 2010, pp. 784–789.

Enhancement of Power Quality in Distribution System using D-Statcom

ABSTRACT:

STATCOM (static synchronous compensator) as a shunt-link flexible AC transmission system(FACTS) controller has shown extensive feasibility in terms of cost-effectiveness in a wide range of problem solving abilities from transmission to distribution levels. Advances in power electronic technologies such as Voltage Source Converter (VSC) improves the reliability and functionality of power electronic based controllers hence resulting in increased applications of STATCOM. In this paper, design and implementation of a Distribution type, Voltage Source Converter (VSC) based static synchronous compensator (DSTATCOM) has been carried out. It presents the enhancement of power quality problems, such as voltage sag and swell using Distribution Static Compensator (D-STATCOM) in distribution system. The model is based on Sinusoidal Pulse Width Modulation (SPWM) technique. The control of the Voltage Source Converter (VSC) is done with the help of SPWM.

The main focus of this paper is to compensate voltage sag and swell in a distribution system. To solve this problem custom power devices are used such as Fixed Compensators (FC, FR), Synchronous Condenser, SVC, SSSC, STATCOM etc. Among these devices Distribution STATCOM (DSTATCOM) is the most efficient and effective modern custom power device used in power distribution networks. DSTATCOM injects a current into the system to mitigate the voltage sag and swell. The work had been carried out in MATLAB environment using Simulink and SIM power system tool boxes. The proposed D-STATCOM model is very effective to enhance the power quality of an isolated distribution system feeding power to crucial equipment in remote areas. The simulations were performed and results were found to be satisfactory using MATLAB/SIMULINK

KEYWORDS:

1.      Statcom

2.      Facts Controllers

3.      D-Statcom

4.      Voltage Source Converter

5.      Total Harmonic Distortions

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig.1 Schematic diagram of D-STATCOM

EXPECTED SIMULATION RESULTS:

Fig.2 Three Phase to Ground -Voltage at Load Point is 0.6600 p.u

Fig.3 Double Line to Ground- Voltage at Load Point is 0.7070 p.u

Fig.4 Line to Line- Voltage at Load Point is 0.7585

Fig.5 Single Line to Ground- Voltage at Load Point is 0.8257

Fig.6 The waveforms shows THD (41.31%) results of fixed load and variable inductive load.

Fig.7 The wave forms shows THD (21.28%) results of fixed load and variable capacitive load

Fig.8 Three Phase to Ground-Voltage at Load Point is 0.9367 p.u

Fig.9 Double Line to Ground- Voltage at Load Point is0.9800 p.u

Fig.10 Line to Line- Voltage at Load Point is 1.068

Fig.11 Single Line to Ground - Voltage at Load Point is 0.9837

Fig.12 The waveform for pure inductive,capacitive loads with statcom

Fig.13 The waveform for without filter THD results 41.31%

Fig.14 The above waveform for with filter THD results 1.11%

CONCLUSION:

The simulation results show that the voltage sags can be mitigate by inserting D-STATCOM to the distribution system. By adding LCL Passive filter to D-STATCOM, the THD reduced. The power factors also increase close to unity. Thus, it can be concluded that by adding DSTATCOM with LCL filter the power quality is improved.

REFERENCES:

[1] A.E. Hammad, Comparing the Voltage source capability of Present and future Var Compensation Techniques in Transmission System, IEEE Trans, on Power Delivery. Volume 1. No.1 Jan 1995.

[2] G.Yalienkaya, M.H.J Bollen, P.A. Crossley, “Characterization of Voltage Sags in Industrial Distribution System”, IEEE transactions on industry applications, volume 34, No. 4, July/August, PP.682-688, 1999

[3] Haque, M.H., “Compensation of Distribution Systems Voltage sags by DVR and D STATCOM”, Power Tech Proceedings, 2001 IEEE Porto, Volume 1, PP.10-13, September 2001.

[4] Anaya-Lara O, Acha E., “Modeling and Analysis Of Custom Power Systems by PSCAD/EMTDC”, IEEE Transactions on Power Delivery, Volume 17, Issue: 2002, Pages: 266 272.

[5] Bollen, M.H.J.,”Voltage sags in Three Phase Systems”, Power Engineering Review, IEEE, Volume 21, Issue: 9, September 2001, PP: 11-

A Voltage Regulator for Power Quality Improvement in Low-Voltage Distribution Grids

ABSTRACT:

This paper presents a voltage-controlled DSTATCOM-based voltage regulator for low voltage distribution grids. The voltage regulator is designed to temporarily meet the grid code, postponing unplanned investments while a definitive solution could be planned to solve regulation issues. The power stage is composed of a three-phase four-wire Voltage Source Inverter (VSI) and a second order low-pass filter. The control strategy has three output voltage loops with active damping and two dc bus voltage loops. In addition, two loops are included to the proposed control strategy: the concept of Minimum Power Point Tracking (mPPT) and the frequency loop. The mPPT allows the voltage regulator to operate at the Minimum Power Point (mPP), avoiding the circulation of unnecessary reactive compensation. The frequency loop allows the voltage regulator to be independent of the grid voltage information, especially the grid angle, using only the information available at the Point of Common Coupling (PCC). Experimental results show the regulation capacity, the features of the mPPT algorithm for linear and nonlinear loads and the frequency stability.

KEYWORDS:

1.      DSTATCOM

2.      Frequency Compensation

3.      Minimum Power Point Tracker

4.      Power Quality

5.      Static VAR Compensators

6.      Voltage Control

7.      Voltage Regulation

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

 Fig. 1. Low voltage distribution grid under analysis with the voltage regulator

EXPECTED SIMULATION RESULTS:

Fig. 2. Dc bus voltages during the DSTATCOM initialization

Fig. 3. PCC voltages without compensation for linear loads

Fig. 4. PCC voltages with compensation for linear loads

Fig. 5. Voltage regulator currents for linear loads

Fig. 6. Grid, load and voltage regulator currents for linear loads

Fig. 7. PCC voltages without compensation for nonlinear loads

Fig. 8. PCC voltages with compensation for nonlinear loads

Fig. 9. Voltage regulator currents for nonlinear loads

Fig. 10. Grid, load and voltage regulator currents for nonlinear loads

Fig. 11. PCC rms value with linear loads

Fig. 12. Processed apparent power with linear loads

Fig. 13. Voltage regulator currents with mPPT enabled for linear loads

Fig. 14. PCC rms value with nonlinear loads

Fig. 15. Processed apparent power with nonlinear loads

Fig. 16. Voltage regulator currents with mPPT enabled for nonlinear loads

Fig. 17. Total dc bus voltage, PCC voltage, grid voltage and voltage regulator current waveforms of a-phase with mPPT enabled with grid swell

Fig. 18. (a) Total dc bus voltage, PCC voltage, grid voltage and voltage regulator current waveforms of a-phase and (b) detail of total dc bus voltage performance with mPPT enabled with grid sag

CONCLUSION:

This paper presents a three phase DSTATCOM as a voltage regulator and its control strategy, composed of the conventional loops, output voltage and dc bus regulation loops, including the voltage amplitude and the frequency loops.

Experimental results demonstrate the voltage regulation capability, supplying three balanced voltages at the PCC, even under nonlinear loads.

The proposed amplitude loop was able to reduce the voltage regulator processed apparent power about 51 % with nonlinear load and even more with linear load (80%). The mPPT algorithm tracked the minimum power point within the allowable voltage range when reactive power compensation is not necessary. With grid voltage sag and swell, the amplitude loop meets the grid code. The mPPT can also be implemented in current-controlled DSTATCOMs, achieving similar results.

The frequency loop kept the compensation angle within the analog limits, increasing the autonomy of the voltage regulator, and the dc bus voltage regulated at nominal value, thus minimizing the dc bus voltage steady state error. Simultaneous operation of the mPPT and the frequency loop was verified.

The proposed voltage regulator is a shunt connected solution, which is tied to low voltage distribution grids without any power interruption to the loads, without any grid voltage and impedance information, and provides balanced and low-THD voltages to the customers.

REFERENCES:

[1] ANEEL National Electric Power Distribution System Procedures – PRODIST, Module 8: Energy Quality. Revision 07, 2014.

[2] M. Mishra, A. Ghosh and A. Joshi, “Operation of a DSTATCOM in voltage control mode,” IEEE Trans. Power Del., vol. 18, no. 1, pp. 258-264, Jan. 2003.

[3] G. Ledwich and A. Ghosh, “A flexible DSTATCOM operating in voltage or current control mode,” IEE Proc.-Gener., Transmiss. Distrib., vol. 149, n. 2, pp. 215-224, Mar. 2002.

[4] T. P. Enderle, G. da Silva, C. Fischer, R. C. Beltrame, L. Schuch, V. F. Montagner and C. Rech, “D-STATCOM applied to single-phase distribution networks: Modeling and control,” in Proc. IEEE Ind. Electron. Soc. Annu. Conf., Oct. 2012, pp. 321 - 326.

[5] C. Kumar and M. Mishra, “Energy conservation and power quality improvement with voltage controlled DSTATCOM,” in Proc. Annu. IEEE India Conf., Dec. 2013 pp. 1-6.