An Intelligent Fuzzy Sliding Mode Controller for aBLDC Motor

ABSTRACT:  

Brushless DC (BLDC) motors are one of the most widely used motors, not only because of their efficiency, and torque characteristics, but also because they have the advantages of being a direct current (DC) supplied, eliminating the disadvantages of using Brushes. BLDC motors have a very wide range of speed, so speed control is a very important issue for it. Sliding mode control (SMC) is one of the popular strategies to deal with uncertain control systems. The Fuzzy Sliding Mode Controller (FSMC) combines the intelligence of a fuzzy inference system with the sliding mode controller. In this paper, an intelligent Fuzzy Sliding Mode controller for the speed control of BLDC motor is proposed. The mathematical model of the BLDC motor is developed and it is used to examine the performance of this controller. Conventionally PI controllers are used for the speed control of the BLDC motor. When Fuzzy SMC is used for the speed control of BLDC motor, the peak overshoot is completely eliminated which is 3% with PI controller. Also the rise time is reduced from 23 ms to 4 ms and the settling time is reduced from 46 ms to 4 ms by applying FMSMC. This paper emphasizes on the effectiveness of speed control of BLDC motor with Fuzzy Sliding Mode Controller and its merit over conventional PI controller.

KEYWORDS:

  1. BLDC motors
  2. Sliding Mode Control
  3. Fuzzy Sliding Mode controller
  4. PI Controller

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig 1 Block diagram of BLDC speed control.

EXPECTED SIMULATION RESULTS:

 

Fig 2 Step response with Fuzzy SMC and Fuzzy PI and PI Controllers

Fig 3 Current in the three phases

 

CONCLUSION:

 Fuzzy sliding mode controller for the speed control of BLDC motor is designed and its performance comparison with PI controller is carried out in this paper. Conventionally PI controllers are used for the speed control of BLDC motor and they give moderate performance under undisturbed conditions even though they are very simple to design and easy to implement. But their performance is poor under disturbed condition like sudden changes in reference speed and sudden change in load. The BLDC motor with PI controller shows large overshoot, high settling time and comparatively large  speed variation under loaded condition.

The Fuzzy Sliding Mode Controller combines the intelligence of fuzzy logic with the Sliding Mode technique. The peak overshoot is completely eliminated and the rise time and settling time are improved when Fuzzy SMC is applied for the speed control of BLDC motor. The fluctuation in speed of the motor under loaded condition is also reduced when fuzzy SMC is applied. Thus this controller becomes an ideal choice for applications where very precise and fine control is required.

REFERENCES:

[1] Neethu U., Jisha V. R., “Speed Control of Brushless DC Motor : A Comparative Study”, IEEE International Conference on Power  Electronics, Drives and Energy Systems, Vol. 8, No. 12, 16-19 December 2012, Bengaluru India.

[2] Chee W. Lu, “T orque Controller for Brushless DC Motors”, IEEE Transactions on Industrial Electronics, Vol. 46, No. 2, April 1999.

[3] Tony Mathew, Caroline Ann Sam, ”Closed Loop Control of BLDC Motor Using a Fuzzy Logic Controller and Single Current Sensor”, International Conference on Advanced Computing and Communication Systems (ICACCS), Vol. 2, No. 13, 19-21 December 2013, Coimbatore India.

[4] T . Raghu, S. Chandra Sekhar, J. Srinivas Rao,“SEPIC Converter based – Drive for Unipolar BLDC Motor”, International Journal of Electrical  and Computer Engineering (IJECE), Vol.2, No.2, April 2012, pp. 159- 165.

[5] M. A. Jabbar, Hla Nu Phyu, Zhejie Liu, Chao Bi, “Modelling and Numerical Simulation of a Brushless Permanent – Magnet DC Motor in Dynamic Conditions by Time – Stepping T echnique”, IEEE Transactions on Industry Applications, Vol. 40, no. 3, MAY/JUNE 2004.

Design of an Efficient Dynamic Voltage Restorer for Compensating Voltage Sags, Swells, and Phase Jumps

ABSTRACT:  

This paper presents a novel design of a dynamic voltage restorer (DVR) which mitigate voltage sags, swell and phase jumps by injecting minimum active power in system and provides the constant power at load side without any disturbance. The design of this compensating device presented here includes the combination of P WM-based control scheme, d q 0 transformation and PI controller in control part of its circuitry, which enables it to minimize the power rating and to response promptly to voltage quality problems faced by today’s electrical power industries.

An

immense knowledge of power electronics was applied in order to design and model of a complete test system solely for analyzing and studying the response of this efficient DVR. In order to realize this control scheme of DVR MAT LAB/SIM U LINK atmosphere was used. The results of proposed design of DVR’s control scheme are compared with the results of existing classical DVR which clearly demonstrate the successful compensation of voltage quality problems by injecting minimum active power.

BLOCK DIAGRAM:

 

 Fig.1. Block Diagram of DVR

 EXPECTED SIMULATION RESULTS:

 

Fig.2.Source Voltage with Sag of 0.5 p.u.

Fig.3.Load Voltage after Compensation through proposed DVR

Fig.4. Load Voltage after Compensation through classical DVR

Fig.5. Voltage injected by proposed DVR as response of Sag

Fig.6.Source Voltage with Swell of 1.5 p.u.

Fig.7. Load Voltage after compensation through proposed DVR

Fig.8. Load Voltage after Compensation through classical DVR

Fig.9. Voltage injected by DVR as response of Swell

Fig.10. .Load Voltage after Compensation of Phase jump

Fig.11. d q 0 form of difference voltage obtained by proposed DVR

Fig.12. d q 0 form of difference voltage obtained by classical DVR

CONCLUSION:

As the world is moving towards modernization, the most essential need that it has is of an efficient and reliable power of excellent quality. Nowadays, more and more sophisticated devices are being introduced, and their sensitivity is  dependent upon the quality of input power. Because even a slight disturbance in power quality, such as Voltage sags, voltage swells, and harmonics, which lasts in tens of milliseconds, can result in a huge loss because of the failure of end use equipment s. For catering such voltage quality problems an efficient DVR is proposed in this paper with the capability of mitigating voltage sags, swells, and phase jumps by injecting minimum active power hence decreasing the VA rating of DVR.

REFERENCES

[1] K u m  a r, R. A nil, G. Siva K u mar, B. K a l y an K u mar, and Ma he sh K. Mi s h  R a. “Compensation of voltage sags and harmonics with phase jumps through DVR with minimum VA rating using Particle Swarm Optimization.” In Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on, pp. 1361-1366. IEEE, 2009.
[2] Song song, Chen, Wang Jian wei, Ga o Wei, and Hu Xiaoguang. “Research and design of dynamic voltage restorer.” In Industrial Informatics (INDIN), 2012 10th IEEE International Conference on, pp. 408-412. IEEE, 2012.
[3] A. Bendre, D. Divan, W. Kranz, and W. E. Brumsickle, “Are Voltage Sags Destroying Equipment?,” IEEE Industry Applications Magazine, vol. 12, pp. 12-21, July-August 2006.

 

Simulation Analysis of DVR Performance for Voltage Sag Mitigation

ABSTRACT:

Voltage sag is truly one of intensity quality issue and it end up extreme to mechanical clients. Voltage hang can cause miss task to a few touchy electronic types of gear. That issue can be moderating with voltage infusion strategy utilizing custom power gadget, Dynamic Voltage Restorer (DVR). This paper presents displaying and investigation of a DVR with heartbeat width tweak (PWM) based controller utilizing Matlab/Simulink. The execution of the DVR relies upon the effectiveness of the control strategy associated with exchanging the inverter. This paper proposed two control procedures which is PI Controller (PI) and Fuzzy Logic Controller (FL). Complete outcomes are introduced to evaluate the execution of every controller as the best power quality arrangement. Different components that likewise can influence the execution and ability of DVR are displayed also.

 

 BLOCK DIAGRAM:

 Figure1. DVR Modelling using Matlab/Simulink

 EXPECTED SIMULATION RESULTS:

Figure 2. (a) Injection voltage from DVR controlled by PI ; (b) injection voltage controlled by FL

Figure 3. (a) Output voltage at load 1 after injection voltage from DVR controlled by PI; (b) Output voltage at load 1after injection voltage controlled by FL.

Figure 4. (a) Injection voltage from DVR controlled by PI; (b) injection voltage controlled by FL.

Figure 5. (a) Output voltage at load 1 after injection voltage from DVR controlled by PI; (b) Output voltage at load 1after injection voltage controlled by FL.

Figure 6. THD generated when PI controller is applied

Figure 7. THD generated when FL controller is applied.

CONCLUSION:

In this examination, the displaying and reenactment of DVR controlled by PI and FL Controller has been produced utilizing Matlab/Simulink. For both controller, the reenactment result demonstrates that the DVR repays the hang rapidly (70μs) and gives great voltage direction. DVR handles numerous types, adjusted and unequal blame with no troubles and infuses the proper voltage segment to address any blame circumstance happened in the supply voltage to keep the heap voltage adjusted and steady at the ostensible esteem. The two controllers demonstrate an incredible execution and create low THD (<5%). Notwithstanding, it very well may be seen that FL Controller gives better execution with THD produced with just 0.64% while PI created 1.68% THD. In any case, other a few factors that can influence the execution of DVR should be tended to for improvement of the yield voltage. These variables are the vitality stockpiling limit and transformer rating. From the recreation, it unmistakably demonstrates the significance of these two factors and how they influence the execution of DVR. Hence, with regards to usage, it is urgent to think about these elements, so the execution of DVR is enhanced.

Performance Analysis of DVR, DSTATCOM and UPQC For Improving The Power Quality With Various Control Strategies

ABSTRACT:

Here, we have examined the voltage quality enhancement techniques by utilizing Dynamic Voltage Restorer (DVR), Distribution Static Synchronous Compensator (D-STATCOM) and Unified Power Quality Conditioner (UPQC) utilizing two distinctive controller Strategies. The controllers utilized are Proportional Integral Controller (PIC) and Fuzzy Logic Controller (FLC). A PI Controller computes a mistake an incentive as the distinction between a deliberate variable and wanted set point. The fluffy rationale controller has continuous sources of info estimated at each example time, named mistake and blunder rate and one yield named activating sign for each stage. The information signals are fuzzified and spoken to in fluffy set documentations as capacities. The characterized ‘If … At that point .. .’ rules deliver yield impelling signs and these signs are defuzzified to simple control signals for contrasting with a transporter motion with control PWM inverter.

 

 BLOCK DIAGRAM:

Fig 1. The equivalent circuit diagram of DVR

 

Fig 2. The equivalent circuit diagram of DST A TCOM

Fig 3.The circuit diagram of UPQC

 EXPECTED SIMULATION RESULTS:

 

Fig 4. Input voltage and input current waveform without compensation

 

Fig 5. Load voltage and load current waveform without compensation

Fig 6. load voltage and load current waveform after compensation(DVR)

Fig 7. Output load voltage without compensation

Fig 8. Output load voltage with compensation using FLC

Fig 9.load voltage and load current waveform after compensation (D-STATCOM)

Fig 10. Load voltage and load current waveform after compensation (D-STATCOM)

Fig 11. Load voltage and load current waveform for UPQC with PI Controller.

Fig 12 Load voltage and load current waveform with compensation

CONCLUSION:

In this paper, we have considered the arrangement, shunt and arrangement shunt compensators. Execution examination has been finished by looking at the power quality utilizing each compensator. The execution of DVR has been dissected with PI controller the heap voltage amid blame is practically equivalent to the ideal load voltage. Load current greatness is practically equivalent yet at the same time there are a few awkward nature between the stages for a little span of time. DVR have been found to manage voltage under Fuzzy Logic controller. Unmistakably DVR diminishes sounds from load voltage successfully and makes it smooth. Henceforth, it is reasoned that DVR has a tremendous extension in enhancing power quality in appropriation frameworks. DSTATCOM is demonstrated to repay voltage levels under defective conditions. Utilizing PI controller, sounds have been diminished extensively. Be that as it may, current got lopsided for the whole span of time. By utilizing the Fuzzy Logic Controller rather than the PI Controller gives better transient reaction. The DC Link voltage is all of a sudden expanded over the reference esteem. Also, it is taken back to its reference esteem. A decent voltage control is likewise accomplished by actualizing Fuzzy rationale control. Additionally the enduring state is achieved quicker. The control techniques of UPQC were portrayed and contrasted with deference with its execution through reenactment. The power quality issues are nearly decreased. The shut circle control plans of current control, for the proposed UPQC have been examined. Absolute consonant mutilation was broke down and it depicts that the UPQC with fluffy controller gives more effectiveness than alternate procedures.

Balanced Voltage Sag Correction Using Dynamic Voltage Restorer Based Fuzzy Polar Controller

ABSTRACT:

Numerous controllers based fluffy rationale have been connected on electric power framework. As often as possible, time reaction of the fluffy controllers is gradually, on the grounds that the quantity of participation capacities are too much. Many research are proposed to limit the quantity of enrollment work, for example, fluffy polar controller technique. By utilizing this strategy, number of enrollment capacity can be limited, so the time reaction of the controller turn out to be quicker. This paper displays the Dynamic Voltage Restorer (DVR) based Fuzzy Polar Controller Method to remunerate adjusted voltage list. Reenactment results demonstrate this proposed technique can repay adjusted voltage hang superior to PI controller.

 

 BLOCK DIAGRAM:


 Fig. 1. Block diagram of DVR

EXPECTED SIMULATION RESULTS:

 Fig. 2. 50% of voltage sags at bus A

Fig. 3. 50% sags correction using DVR based PI Controller

Fig. 4. 50% sags correction using DVR based fuzzy polar controller

 CONCLUSION:

DVR based PI Controller can keep up half voltage hangs at 110 % and 30% voltage droops at 98%. DVR based Fuzzy Polar Controller can keep up half voltage lists at 100 % and 30% voltage lists at 97%. As per the mistake normal everything being equal, are demonstrated that the execution of DVR based Fuzzy Polar Controller superior to DVR based PI Controller. Further investigation for unbalance remedy is being attempted to demonstrate the viability of the proposed controller.

 

Performance Investigation of Dynamic Voltage Restorer using PI and Fuzzy Controller

ABSTRACT:

This paper researches the execution of Dynamic Voltage Restorer for repaying distinctive voltage droop levels with different flaws and to lessen the Total Harmonic Distortion amid the alleviation procedure. The DVR is actualized with three stage voltage source inverter and is associated at the purpose of normal coupling so as to direct the heap side voltage. The pay depends on PI and Mamdani Fuzzy Controller. Broad reproduction examines under various size of hang for flaws on load side for adjusted and lopsided conditions are directed utilizing shortcoming generator. Reenactment result investigation uncovers that DVR performs consummately with PI and Fuzzy control approach. What’s more, ability and execution of DVR for different vitality stockpiling limits and infusion transformer rating are additionally broke down. The execution of these controllers is approved with recreation results utilizing Matlab/Simulink.

 

BLOCK DIAGRAM:

Fig. 1. Block Diagram of DVR model

 

 EXPECTED SIMULATION RESULTS:

Fig.2 Unbalanced three-phase to ground fault (PI CONTROL)

Figure 3. Unbalanced three-phase to ground fault (FLC)

Fig.4 Single-line-to-ground fault with 50% sag (PI Control)

Fig.5 Single-line-to-ground fault with 50% sag (FLC)

Fig.6 Balanced three-phase fault with 50% sag (PI CONTROL)

Fig.7 Balanced three-phase fault with 50% sag (FLC)

Fig.8 Three Phase fault with nearly 100% sag (PI)

Fig.9 Three Phase fault with nearly 100% sag (FLC)

 

CONCLUSION:

The DVR handles both adjusted and uneven conditions viably and infuses the digressed voltage part under supply unsettling influences to keep the heap voltage adjusted and consistent at the ostensible esteem. In this manner the proposed DVR can alleviate different dimensions of voltage hang and distinctive sorts of shortcomings. Reenactment results in MATLAB/SIMULINK demonstrate that the control conspire gives a precise following of the voltage reference and a quick transient reaction. Both the controllers shows great execution and limit the THD level. It is discovered that FLC gives better execution with THD of 0.42% where as PI gives 0.46% THD. The expansion in KVA rating of infusion transformer and DC stockpiling esteem successfully repays the voltage droop and diminish the THD level. Be that as it may, higher estimation of DC stockpiling and transformer rating makes it increasingly costly. The adequacy of a DVR framework basically relies on the rating of DC stockpiling limit, infusion transformer rating and the heap. From the recreation, it obviously demonstrates the significance of these components and how it influences the execution of DVR is dissected.

A Novel Design of PI Current Controller for PMSG-based Wind Turbine Considering Transient Performance Specifications and Control Saturation

ABSTRACT:

This paper introduces a novel plan procedure of decoupled PI current controller for changeless magnet synchronous generator (PMSG)- based breeze turbines sustaining a lattice fixing inverter through consecutive converter. In particular, the plan procedure comprises of consolidating aggravation eyewitness based control (DOBC) with criticism linearization (FBL) system to guarantee ostensible transient execution recuperation under model vulnerability. By rearranging the DOBC under the input linearizing control, it is demonstrated that the composite controller decreases to a decoupled PI current controller in addition to an extra term that has the primary job of recuperating the ostensible transient execution of the criticism linearization, particularly under advance changes in the reference. Also, an enemy of windup compensator emerges normally into the controller while considering the control input immersion to plan the  DOBC. This licenses to expel the impact of the immersion squares required to constrain the control input. The proposed control plot is executed and approved through experimentation directed on 22-post, 5 kW PMSG. The outcomes uncovered that the proposed system can effectively accomplish ostensible execution recuperation under model vulnerability just as enhanced transient exhibitions under control immersion.

 

BLOCK DIAGRAM:

 Fig. 1. Configuration of a direct-drive PMSG-based WECS connected

to the host grid.

EXPECTED SIMULATION RESULTS:

 

Fig. 2. System’s response under the composite controller consisting of the feedback controller (13) and the PI-DO (34)–(37). The controller was tested experimentally using the block diagram of Fig. 3. Specifically, the PI-DO (34)–(37) was evaluated with and without the consideration of the reference jump .

Fig. 3. System’s response under the composite controller consisting of the feedback controller (13) and the DOBC (25). The controller was tested experimentally using the block diagram depicted in Fig. 2.

Fig. 4. System’s response under a conventional PI current controller [17].

Fig. 5. Performance evaluation of the proposed PI-DO under model uncertainty.

Fig. 6. Experimental results: Performance testing of the proposed PI current controller under MPPT algorithm, with id (2 A/div), iq (4 A/div), ia (10 A/div), ws (5 [m/s]/div), iga (6 A/div), r (50 [rpm/min]/div), and time (400 ms/div)

CONCLUSION:

This paper has introduced a novel structure of decoupled PI controller to upgrade the transient execution for the present control of PMSG-based breeze turbine. The proposed controller strategy was built up by consolidating a DOBC with criticism linearizing control law. For reasons unknown, the composite controller has a decoupled PI-like structure in addition to two extra parts. The initial segment is fundamentally an enemy of windup compensator, while the second part utilizes the reference bounce data to counteracts the impact of the sudden advance changes in the power request on the transient reaction. This change of the decoupled PI controller grants to ensure zero enduring state blunder without giving up the ostensible transient execution indicated by the state input controller. This remarkable element can’t be accomplished under the current decoupled PI controller, especially when the model parameters are not precise. Trial tests have been performed, and the outcomes bolster the utilization of the reference bounce data to enhance the transient execution under the decoupled PI controller. Along these lines, the proposed methodology furnishes professionals with a substitute strategy in structuring a vigorous decoupled PI current controller for PMSG-based breeze vitality change framework.

Application of Neural Networks in Power Quality

2015 International Conference on Soft Computing Techniques and Implementations- (ICSCTI)

 ABSTRACT: Use of power electronic converters with nonlinear loads produces harmonic currents and reactive power. A shunt active power filter provides an elegant solution to reactive power compensation as well as harmonic mitigation leading to improvement in power quality. However, the shunt active power filter with PI type of controller is suitable only for a given load. If the load is varying, the proportional and integral gains are required to be fine tuned for each load setting. The present study deals with neural network based controller for shunt active power filter. The performance of neural network controller evaluated and compared with PI controller.

 KEYWORDS:

  1. Active Power Filter
  2. Neural Networks
  3. Back Propagation Algorithm
  4. Soft Computing.

 SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

Schematic Diagram of Shunt Active Power Filter

Fig1. Schematic Diagram of Shunt Active Power Filter

  

EXPECTED SIMULATION RESULTS:

 

Fig 2. (a) Waveform of Load Current, Compensating Current, Source Current and Source Voltage for 1kVA with 􀄮=60º and (b) Waveform of Source Voltage and in the phase Source Current of Fig. (a)

 

CONCLUSION:

The active power filter controller with neural network based controller has been seen to eminently minimize harmonics in the source current when the load demands non sinusoidal current, irrespective of whether the load is fixed or varying. Simultaneously, the power factor at source also becomes the unity, if the load demands reactive power. Thus, neural network based controller is far superior to PI type of controller which requires fine tuning of Kp and Ki every time the load changes. In the present work, the performance of a range of values of the load is considered to robustly test the controller. It has been demonstrated that neural network based controller, therefore, significantly improves the performance of a shunt active power filter.

 

REFERENCES:

  • Laszlo Gyugyi, “Reactive Power Generation and Control by Thyristor Circuits”, IEEE Transactions on Industry Applications, vol. IA-15, no. 5, September/October 1979.
  • Akagi, Y. Kanazawa, and A. Nabae, “Instantaneous reactive power compensators comprising switching devices without energy storage components,” IEEE Transaction Industrial Applications, vol. IA-20, pp. 625-630, May/June 1984.
  • Z. Peng, H. Akagi, and A. Nabae, “A study of active power filters using quad series voltage source pwm converters for harmonic compensation,” IEEE Transactions on Power Electronics, vol. 5, no. 1, pp. 9–15, January 1990.
  • Conor A. Quinn, Ned Mohan, “Active Filtering of Harmonic Currents in Three-phase, Four-Wire Systems with Three-phase and Single-phase Non-Linear Loads”, IEEE-1992.
  • A. Morgan, J. W. Dixon, and R. R. Wallace, “A three-phase active power filter operating with fixed switching frequency for reactive power and current harmonic compensation,” IEEE Transactions on Industrial Electronics, vol. 42, no. 4, pp. 402–408, August 1995.

Improved Dynamic Performance of Shunt Active Power Filter Using Particle Swarm Optimization

2017 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT TECHNIQUES IN CONTROL, OPTIMIZATION AND SIGNAL PROCESSING

 ABSTRACT: In this paper, a novel particle swarm optimization (PSO) technique is proposed to tune the proportional-integral (PI) controller gain parameters for enhancing the dynamic performance of the shunt active power filter (APF). The shunt APFs are well established filter to compensate current harmonics, reactive power to maintain the power factor unity. The compensation is highly influenced by the DC-link voltage regulation. The calculated PI controller gain parameters conventionally, are giving satisfactory results under steady state condition of the load. However, tuning of the PI controller parameters under fast changing loads are very difficult. To improve the dynamic performance of the system and optimize the gain parameters of the PI controller, a PSO technique is proposed. The modified p-q theory uses a composite observer filter to extract fundamental component of voltage from the distorted supply voltage for the further process of calculating reference current. A complete comparison of conventional and PSO based PI controller gain tuning have been simulated using MATLAB® Simulink software under different supply voltage and load condition of the system. The results show that the dynamic response is improved with PSO based PI tuning compared to conventional PI tuning.

 KEYWORDS

  1. Shunt Active power filters (SAPF)
  2. PI controller
  3. Particle swarm optimization (PSO)

SOFTWARE: MATLAB/SIMULINK

BLOCK  DIAGRAM:

Fig. 1 Optimal design of PI controller gain values using PSO

EXPECTED SIMULATION RESULTS

Fig. 2. Performance of modified p-q control technique under available supply voltage

Fig. 3 FFT analysis of phase a source current under distorted supply voltage

 

Fig. 4 Simulation results under distorted supply voltage with RC-load

Fig. 5 Harmonic spectrum of phase-a source current after Compensation

Fig. 6 Simulation dynamic performance of the shunt APF

Fig.7 Tuning of PI controller: (a) conventional PI method (b) using PSO technique

 CONCLUSION

The performance of the proposed PSO based modified p-q theory has been designed for different types of loads and supply voltage conditions. The modified composite observer filter is an extracted fundamental frequency component of voltage from distorted supply without phase delay which further processed in the calculation of the reference current. The comparison of conventional PI tuning and PSO based tuning is tested for dynamic condition of the load. The proposed control scheme is modelled in MATLAB simulink environment. The simulation results show that the PSO based tuning provide less overshoot, ripples in the DC-link voltage and lesser settling time as compared to convention PI tuning.

 REFERENCES:

  • S. Adamu, H. S. Muhammad and D.S. Shuaibu, “Harmonics Assessment and Mitigation in Medical Diagnosis Equipment”, IEEE international conference on Awerness Science and Technology (iCAST), pp. 70-75, 2014.
  • Akagi, “Active harmonic filters,” Proc. IEEE, Vol. 93, no.12, pp.2128-2141, pp.2128-2141, 2005.
  • H. Bollen, Understanding Power Quality Problems: Voltage Sags and Interruptions, John Wiley & Sons, 1999.
  • Akagi, E. H. Watanabe, and M. Aredes, Instantaneous Power Theory and Applications to Power Conditioning, Piscataway, NJ: IEEE Press, 2007.
  • Gupta, S. P. Singh and S. P. Dubey “Neural network based shunt active filter for harmonic and reactive power compensation under non-ideal mains voltage,” In proc. of IEEE Industrial Electronics and Applications (ICIEA), Taiwan, pp. 370-375, 2010.

Particle Swarm Optimization Based Shunt Active Harmonic Filter for Harmonic Compensation

2017 4th IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics (UPCON)

ABSTRACT: This paper presents a performance evaluation of Shunt Active Harmonic Filter (SAHF) for harmonic compensation, using Particle Swarm Optimization algorithm for DC link voltage regulation. Particle Swarm Optimization algorithm is used to search for the optimal PI control parameters. The simulation results show that the performance of Shunt Active Harmonic Filter (SAHF), where current is generated using instantaneous real and reactive power(p-q) theory, using PSO technique for six pulse controlled rectifier under different firing angles is simple in structure and very effective for harmonic compensation. The simulation is done with the help of MATLAB-SIMULINK tool box.

KEYWORDS

  1. Shunt Active Harmonic Filter
  2. PI controller
  3. Hysteresis Current Controller
  4. P-q theory
  5. PSO
  6. Controlled rectifier

 SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

Fig. 1. Proposed implementation of PI controller

EXPECTED SIMULATION RESULTS

Fig. 2. Convergence graph of PSO for 􀍲􀍲􀀃firing angle

Fig. 3. FFT analysis of source current (phase a) without SAHF.

Fig. 4. FFT analysis of source current (phase a) of SAHF for 􀍲􀍲firing angle.

Fig. 5. FFT analysis of source current (phase a) of optimized SAHF for

􀍲􀍲firing angle.

 CONCLUSION

It can be concluded from the simulation results that with the application of SAHF in parallel to controlled rectifier, harmonics present in the source current are mostly compensated. The DC link voltage is controlled by PI controller, which when optimized using Particle Swarm Optimization Technique further reduces the THD value of source current. The values of THD in phase a, b and c of source current are 30.18%, 31.54%, 31.74% respectively. Further it is analyzed that by optimizing the gains of PI controller the THD values are further reduced from 2.66% to 1.85% for 􀍲􀍲firing angle. Thus we can clearly state that optimization of PI controller using PSO further reduces the harmonics on the source side.

 

REFERENCES:

[1] M.H.J. Bollen, “What is Power Quality?”, Electric Power Systems Research, Vol.66, Iss. 1, pp. 5-14, July 2003.

[2] H. Akagi, Y. Kanazawa and A. Nabae, ”Theory of Instantaneous Reactive Power and Its Applications”, Transactions of the lEE-Japan, Part B, vol. 103, no.7, 1983, pp. 483-490.

[3] Ned Mohan 2002, ‘Power Electronics: Converters, Applications, and Design’ 3rd Edition’, Wiley publications.

[4] F. Z. Peng, H. Akagi and A. Nabae, “A New Approach to Harmonic Compensation in Power System a Combined System of Shunt Passive and Series Active Filter”, IEEE Trans. On Industry App., vol. 27, no. 6, (1990), pp. 983-990.

[5] Hamadi,A , Rahmani,S & Al-Haddad, K 2010, ‘A hybrid passive filter configuration for VAR control and harmonic compensation’, IEEE Trans. Ind. Electron., 57(7): 2419–2434.