Fuzzy logic Technique Based Speed Control of a Permanent Magnet Brushless DC...IJMER
This paper presents an analysis by which the dynamic performances of a permanent magnet
brushless dc (PMBLDC) motor drive with different speed controllers can be successfully predicted. The
control structure of the proposed drive system is described. The dynamics of the drive system with a
classical proportional-integral-derivative (PID) and Fuzzy-Logic (FL) speed controllers are presented.
The simulation results for different parameters and operation modes of the drive system are investigated
and compared. The results with FL speed controller show improvement in transient response of the
PMBLDC drive over conventional PID controller. Moreover, useful conclusions stemmed from such a
study which is thought of good use and valuable for users of these controllers
Design of Fuzzy Logic Controller for Speed Regulation of BLDC motor using MATLABijsrd.com
Brushless DC (BLDC) motors drives are one of the electrical drives that are rapidly gaining popularity, due to their high efficiency, good dynamic response and low maintenance. The design and development of a BLDC motor drive for commercial applications is presented. The aim of paper is to design a simulation model of inverter fed PMBLDC motor with Fuzzy logic controller. Fuzzy logic controller is developed using fuzzy logic tool box which is available in Matlab. FIS editor used to create .FIS file which contains the Fuzzy Logic Membership function and Rule base. And membership functions of desired output. After creating .FIS file it is implemented in the Matlab Simulink. And the BLDC motor is run satisfactorily using the Fuzzy logic controller.
This paper analyzes the effects of the bilateral control parameters variation on the stability, the transparency and the accuracy, and on the operational force that is applied to DC motor and the master system. The bilateral controller is designed for rehabilitation process. PD controller is used to control the position tracking and a force gain controller is used to control the motor torque. DOB eliminate the internal disturbance and RTOB to estimate the joint torque without using sensors. The system consists of two manipulators, each manipulator has 1dof, master and slave teleoperation system, 4 control-architecture channel, DOB and reaction force observer. The master system is attached to human oberator. The slave system is attached to external load. The aim in this paper is to design the controller so that it requires less force to move the master manipulator and at the same time achieve high performance in position tracking.
Fuzzy logic Technique Based Speed Control of a Permanent Magnet Brushless DC...IJMER
This paper presents an analysis by which the dynamic performances of a permanent magnet
brushless dc (PMBLDC) motor drive with different speed controllers can be successfully predicted. The
control structure of the proposed drive system is described. The dynamics of the drive system with a
classical proportional-integral-derivative (PID) and Fuzzy-Logic (FL) speed controllers are presented.
The simulation results for different parameters and operation modes of the drive system are investigated
and compared. The results with FL speed controller show improvement in transient response of the
PMBLDC drive over conventional PID controller. Moreover, useful conclusions stemmed from such a
study which is thought of good use and valuable for users of these controllers
Design of Fuzzy Logic Controller for Speed Regulation of BLDC motor using MATLABijsrd.com
Brushless DC (BLDC) motors drives are one of the electrical drives that are rapidly gaining popularity, due to their high efficiency, good dynamic response and low maintenance. The design and development of a BLDC motor drive for commercial applications is presented. The aim of paper is to design a simulation model of inverter fed PMBLDC motor with Fuzzy logic controller. Fuzzy logic controller is developed using fuzzy logic tool box which is available in Matlab. FIS editor used to create .FIS file which contains the Fuzzy Logic Membership function and Rule base. And membership functions of desired output. After creating .FIS file it is implemented in the Matlab Simulink. And the BLDC motor is run satisfactorily using the Fuzzy logic controller.
This paper analyzes the effects of the bilateral control parameters variation on the stability, the transparency and the accuracy, and on the operational force that is applied to DC motor and the master system. The bilateral controller is designed for rehabilitation process. PD controller is used to control the position tracking and a force gain controller is used to control the motor torque. DOB eliminate the internal disturbance and RTOB to estimate the joint torque without using sensors. The system consists of two manipulators, each manipulator has 1dof, master and slave teleoperation system, 4 control-architecture channel, DOB and reaction force observer. The master system is attached to human oberator. The slave system is attached to external load. The aim in this paper is to design the controller so that it requires less force to move the master manipulator and at the same time achieve high performance in position tracking.
SPEED AND TORQUE CONTROL OF AN INDUCTION MOTOR WITH ANN BASED DTCijics
Due to advantages such as fast dynamic response, simple and robust control structure, direct torque
control (DTC) is commonly used method in high performance control method for induction motors. Despite
mentioned advantages, there are some chronically disadvantages with this method like high torque and
current ripples, variable switching behaviour and control problems at low speed rates. On the other hand,
artificial neural network (ANN) based control algorithms are getting increasingly popular in recent years
due to their positive contribution to the system performance. The purpose of this paper is investigating of
the effects of ANN integrated DTC method on induction motor performance by numerical simulations. For
this purpose, two different ANN models have been designed, trained and implemented for the same DTC
model. The first ANN model was designed to select optimum inverter and the second model was designed to
use in the determination of the flux vector position. Matlab/Simulink model of the proposed ANN based
DTC method was created in order to compare with the conventional DTC and the proposed DTC methods.
The simulation studies proved that the induction motor torque ripples have been reduced remarkably with
the proposed method and this approach can be a good alternative to the conventional DTC method for
induction motor control.
Comparison of different controllers for the improvement of Dynamic response o...IJERA Editor
As the technology is fast changing, there is more and more use of machine intelligence in modern motor controllers. These controllers are employed in advanced electric motor drives in particular, the present day Induction motor drives. These systems emulate the human logic. This is particularly useful when the application has poorly defined mathematical model. In this present paper the analysis of fuzzy logic as the artificial intelligence is used. The comparative study of Fuzzy PI, Fuzzy MRAC is made. There is always a compromise of the cost and complexity. So this paper presents a new approach and its dynamic response in comparison to the Fuzzy PI and Fuzzy MRAC. The proposed controller is Fuzzy PI with scaling factors. This approach is validated with the Speed, torque responses of Indirect vector controlled Induction motor (IVCIM) drive.
To design and implementation of variable and constant with no load for induction motor (IM) that is the goal in this work. This paper was including three parts, first the simulation model with no load for IM, Second the simulation model with constant load for IM, Third the simulation model with variable load for IM. In addition, this work includes comparative between two different controllers (PI and fuzzy logic control (FLC). The simulation results clearly the implementation of variable and constant with no load for IM. The simulation response of the system achieves better results when choosing to use type fuzzy-PI controller technique comparison with conventional PI controller and improve the performance of the system at different operation conditions.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Integrated fuzzylogic controller for a Brushless DC Servomotor systemEhab Al hamayel
This presentation discusses the designing and simulation of "Integrated fuzzylogic controller for a Brushless DC Servomotor system" using Matlab simulink
Speed Control of Brushless Dc Motor Using Fuzzy Logic Controlleriosrjce
This paper presents a control scheme of a fuzzy logic for the brushless direct current (BLDC)
permanent magnet motor drives. The mathematical model of BLDC motor and fuzzy logic algorithm is derived.
The controller is designed to tracks variations of speed references and stabilizes the output speed during load
variations. The BLDC has some advantages compare to the others type of motors, however the nonlinearity of
the BLDC motor drive characteristics, because it is difficult to handle by using conventional proportionalintegral
(PI) controller. The BLDC motor is fed from the inverter where the rotor position and current
controller is the input. In order to overcome this main problem, the fuzzy logic control is learned continuously
and gradually becomes the main effective control. The effectiveness of the proposed method is verified by
develop simulation model in MATLAB-Simulink program. The simulation results show that the proposed fuzzy
logic controller (FLC) produce significant improvement control performance compare to the PI controller for
both condition controlling speed reference variations and load disturbance variations. Fuzzy logic is introduced
in order to suppressing the chattering and enhancing the robustness of the controlled system. Fuzzy boundary
layer is developed to provide smother transition to the equivalent control. Smaller overshoot in the speed
response and much better disturbance rejecting capabilities.
DESIGN OF FAST TRANSIENT RESPONSE, LOW DROPOUT REGULATOR WITH ENHANCED STEADY...ijcsitcejournal
Design and implementation of control systems for power supplies require the use of efficient techniques that
provide simple and practical solutions in order to fulfill the performance requirements at an acceptable cost.
Application of manual methods of system identification in determining optimal values of controller settings is
quite time-consuming, expensive and, sometimes, may be impossible to practically carry out. This paper
describes an analytical method for the design of a control system for a fast transient response, low dropout
(LDO) linear regulated power supply on the basis of PID compensation. The controller parameters are
obtained from analytical model of the regulator circuit. Test results showed good dynamic characteristics
with adequate margin of stability. This study shows that PID parameter values sufficiently close to optimum
can easily be obtained from analytical study of the regulator system. The applied method of determining
controller settings greatly reduces design time and cost.
Speed Conrol of Separately Excited dc Motor using Fuzzy TechniqueIDES Editor
This paper presents the speed control of a separately
excited DC motor using Fuzzy Logic Control (FLC). The Fuzzy
Logic Controller designed in this study applies the required
control voltage based on motor speed error (e) and its change
(ce). The performance of the driver system was evaluated
through digital simulations using Simulink. The simulation
results show that the control with FLC outperforms PI control
in terms of overshoot, steady state error and rise time.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Permanent magnet direct current motors (PMDCM) are widely used in various applications such as space technologies, personal computers, medical, military, robotics, electrical vehicles, etc. In this paper, the mathematical model of PMDCM is designed and simulated using MATLAB software. The PMDCM speed is controlled using rate feedback controller due to its ability of improving system damping. To improve the controller performance, it’s parameters are tuned using genetic algorithm (GA) and direct search (DS) techniques. The tuning process based on different performance criteria. The most four common performance criteria used in this paper are JIAE (Integral of Absolute Error), JISE (Integral of Square Error), JITAE (Integral of Time-Weighted Absolute Error), and JITSE (Integral of Time-Weighted Square Error). The results obtained from these evolutionary techniques are compared. The results show an obvious improvement in system performance including enhancing the transient and steady state of PMDCM speed responses for all performance criteria.
Type 1 versus type 2 fuzzy logic speed controllers for brushless DC motors IJECEIAES
This work presented two fuzzy logic (FL) schemes for speed-controlled brushless DC motors. The first controller is a Type 1 FL controller (T1FLC), whereas the second controller is an interval Type 2 FL controller (IT2FLC). The two proposed controllers were compared in terms of system dynamics and performance. For a fair comparison, the same type and number of membership functions were used for both controllers. The effectiveness of the structures of the two FL controllers was verified through simulation in MATLAB/SIMULINK environment. Simulation result showed that IT2FLC exhibited better performance than T1FLC.
This paper introduces experimental comparison study between six and four switch inverter fed three phase induction motor drive system. The control strategy of the drive is based on speed sensoreless vector control using model reference adaptive system as a speed estimator. The adaptive mechanism of speed control loop depends on fuzzy logic control. Four switch inverter conFigureurations reduces the cost of the inverter, the switching losses, the complexity of the control algorithms, interface circuits, the computation of real-time implementation, volume-compactness and reliability of the drive system. The robustness of the proposed model reference adaptive system based on four switch three-phase inverter (FSTPI) fed induction motor drive is verified experimentally at different operating conditions. Experimental work is carried using digital signal processor (DSP1103) for a 1.1 kW motor. A performance comparison of the proposed FSTP inverter fed IM drive with a conventional six switch three-phase inverter (SSTP) inverter system is also made in terms of speed response. The results show that the proposed drive system provides a fast speed response and good disturbance rejection capability. The proposed FSTP inverter fed IM drive is found quite acceptable considering its performance, cost reduction and other advantages features.
IOSR Journal of Humanities and Social Science is an International Journal edited by International Organization of Scientific Research (IOSR).The Journal provides a common forum where all aspects of humanities and social sciences are presented. IOSR-JHSS publishes original papers, review papers, conceptual framework, analytical and simulation models, case studies, empirical research, technical notes etc.
Proximate, Mineral and Anti-Nutrient Evaluation of Pumpkin Pulp (Cucurbita Pepo)IOSR Journals
Abstract: Proximate, minerals and anti-nutritional concentration of Pumpkin pulp (Cucurbita pepo) were investigated using standard analytical methods as stipulated by AOAC (1990), Agte el al; (1995), Chapman and Pratt, (1961), Kadhakrishna and Sivaprasad (1980), Nelson (1968),Day and underwood, (1986). The proximate composition (%) showed that pumpkin pulp contained Total ash 15.988 ± 0.10, Moisture 0.532 ± 0.10, Fat extract 2.300 ± 0.01 Crude fibre 11.463 ± 0.10, Crude protein 3.070 ± 0.01 and Carbohydrate by difference 66.647 ± 0.01% .The mineral element were Mg, Ca, Mn, Fe, Cu, Pb, Ni and P with values of 189.91 ± 0.2, 179.01 ± 0.2, 0.502 ± 0.1, 1.370 ± 0.1, 3.910 ± 0.1, 0.290 ± 0.1, 0.110 ± o.1 and 11.83 ± 0.2 mg/kg respectively also Na and K with values of 159.01 ± 0.2 and K 160.31 ± 0.1 mg/l00kg were estimated using Flame Emission spectrophotometer. The anti-nutritional analysis of pumpkin pulp gives Phytates 0.618 ± 0.100mgl100kg, Oxalates 16.297 ± 0.100 mg/100kg and Tannins 0.358 ± 0.100 mg/100kg. The results obtained above goes a long way to proof that pumpkin pulp is highly nutritious and at the same time can be used as food formulation for infant due to its nutritional composition.
Key Words: Cucurbita pepo, cucurbitaceae, pumpkin pulp, proximate analysis, mineral
SPEED AND TORQUE CONTROL OF AN INDUCTION MOTOR WITH ANN BASED DTCijics
Due to advantages such as fast dynamic response, simple and robust control structure, direct torque
control (DTC) is commonly used method in high performance control method for induction motors. Despite
mentioned advantages, there are some chronically disadvantages with this method like high torque and
current ripples, variable switching behaviour and control problems at low speed rates. On the other hand,
artificial neural network (ANN) based control algorithms are getting increasingly popular in recent years
due to their positive contribution to the system performance. The purpose of this paper is investigating of
the effects of ANN integrated DTC method on induction motor performance by numerical simulations. For
this purpose, two different ANN models have been designed, trained and implemented for the same DTC
model. The first ANN model was designed to select optimum inverter and the second model was designed to
use in the determination of the flux vector position. Matlab/Simulink model of the proposed ANN based
DTC method was created in order to compare with the conventional DTC and the proposed DTC methods.
The simulation studies proved that the induction motor torque ripples have been reduced remarkably with
the proposed method and this approach can be a good alternative to the conventional DTC method for
induction motor control.
Comparison of different controllers for the improvement of Dynamic response o...IJERA Editor
As the technology is fast changing, there is more and more use of machine intelligence in modern motor controllers. These controllers are employed in advanced electric motor drives in particular, the present day Induction motor drives. These systems emulate the human logic. This is particularly useful when the application has poorly defined mathematical model. In this present paper the analysis of fuzzy logic as the artificial intelligence is used. The comparative study of Fuzzy PI, Fuzzy MRAC is made. There is always a compromise of the cost and complexity. So this paper presents a new approach and its dynamic response in comparison to the Fuzzy PI and Fuzzy MRAC. The proposed controller is Fuzzy PI with scaling factors. This approach is validated with the Speed, torque responses of Indirect vector controlled Induction motor (IVCIM) drive.
To design and implementation of variable and constant with no load for induction motor (IM) that is the goal in this work. This paper was including three parts, first the simulation model with no load for IM, Second the simulation model with constant load for IM, Third the simulation model with variable load for IM. In addition, this work includes comparative between two different controllers (PI and fuzzy logic control (FLC). The simulation results clearly the implementation of variable and constant with no load for IM. The simulation response of the system achieves better results when choosing to use type fuzzy-PI controller technique comparison with conventional PI controller and improve the performance of the system at different operation conditions.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Integrated fuzzylogic controller for a Brushless DC Servomotor systemEhab Al hamayel
This presentation discusses the designing and simulation of "Integrated fuzzylogic controller for a Brushless DC Servomotor system" using Matlab simulink
Speed Control of Brushless Dc Motor Using Fuzzy Logic Controlleriosrjce
This paper presents a control scheme of a fuzzy logic for the brushless direct current (BLDC)
permanent magnet motor drives. The mathematical model of BLDC motor and fuzzy logic algorithm is derived.
The controller is designed to tracks variations of speed references and stabilizes the output speed during load
variations. The BLDC has some advantages compare to the others type of motors, however the nonlinearity of
the BLDC motor drive characteristics, because it is difficult to handle by using conventional proportionalintegral
(PI) controller. The BLDC motor is fed from the inverter where the rotor position and current
controller is the input. In order to overcome this main problem, the fuzzy logic control is learned continuously
and gradually becomes the main effective control. The effectiveness of the proposed method is verified by
develop simulation model in MATLAB-Simulink program. The simulation results show that the proposed fuzzy
logic controller (FLC) produce significant improvement control performance compare to the PI controller for
both condition controlling speed reference variations and load disturbance variations. Fuzzy logic is introduced
in order to suppressing the chattering and enhancing the robustness of the controlled system. Fuzzy boundary
layer is developed to provide smother transition to the equivalent control. Smaller overshoot in the speed
response and much better disturbance rejecting capabilities.
DESIGN OF FAST TRANSIENT RESPONSE, LOW DROPOUT REGULATOR WITH ENHANCED STEADY...ijcsitcejournal
Design and implementation of control systems for power supplies require the use of efficient techniques that
provide simple and practical solutions in order to fulfill the performance requirements at an acceptable cost.
Application of manual methods of system identification in determining optimal values of controller settings is
quite time-consuming, expensive and, sometimes, may be impossible to practically carry out. This paper
describes an analytical method for the design of a control system for a fast transient response, low dropout
(LDO) linear regulated power supply on the basis of PID compensation. The controller parameters are
obtained from analytical model of the regulator circuit. Test results showed good dynamic characteristics
with adequate margin of stability. This study shows that PID parameter values sufficiently close to optimum
can easily be obtained from analytical study of the regulator system. The applied method of determining
controller settings greatly reduces design time and cost.
Speed Conrol of Separately Excited dc Motor using Fuzzy TechniqueIDES Editor
This paper presents the speed control of a separately
excited DC motor using Fuzzy Logic Control (FLC). The Fuzzy
Logic Controller designed in this study applies the required
control voltage based on motor speed error (e) and its change
(ce). The performance of the driver system was evaluated
through digital simulations using Simulink. The simulation
results show that the control with FLC outperforms PI control
in terms of overshoot, steady state error and rise time.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Permanent magnet direct current motors (PMDCM) are widely used in various applications such as space technologies, personal computers, medical, military, robotics, electrical vehicles, etc. In this paper, the mathematical model of PMDCM is designed and simulated using MATLAB software. The PMDCM speed is controlled using rate feedback controller due to its ability of improving system damping. To improve the controller performance, it’s parameters are tuned using genetic algorithm (GA) and direct search (DS) techniques. The tuning process based on different performance criteria. The most four common performance criteria used in this paper are JIAE (Integral of Absolute Error), JISE (Integral of Square Error), JITAE (Integral of Time-Weighted Absolute Error), and JITSE (Integral of Time-Weighted Square Error). The results obtained from these evolutionary techniques are compared. The results show an obvious improvement in system performance including enhancing the transient and steady state of PMDCM speed responses for all performance criteria.
Type 1 versus type 2 fuzzy logic speed controllers for brushless DC motors IJECEIAES
This work presented two fuzzy logic (FL) schemes for speed-controlled brushless DC motors. The first controller is a Type 1 FL controller (T1FLC), whereas the second controller is an interval Type 2 FL controller (IT2FLC). The two proposed controllers were compared in terms of system dynamics and performance. For a fair comparison, the same type and number of membership functions were used for both controllers. The effectiveness of the structures of the two FL controllers was verified through simulation in MATLAB/SIMULINK environment. Simulation result showed that IT2FLC exhibited better performance than T1FLC.
This paper introduces experimental comparison study between six and four switch inverter fed three phase induction motor drive system. The control strategy of the drive is based on speed sensoreless vector control using model reference adaptive system as a speed estimator. The adaptive mechanism of speed control loop depends on fuzzy logic control. Four switch inverter conFigureurations reduces the cost of the inverter, the switching losses, the complexity of the control algorithms, interface circuits, the computation of real-time implementation, volume-compactness and reliability of the drive system. The robustness of the proposed model reference adaptive system based on four switch three-phase inverter (FSTPI) fed induction motor drive is verified experimentally at different operating conditions. Experimental work is carried using digital signal processor (DSP1103) for a 1.1 kW motor. A performance comparison of the proposed FSTP inverter fed IM drive with a conventional six switch three-phase inverter (SSTP) inverter system is also made in terms of speed response. The results show that the proposed drive system provides a fast speed response and good disturbance rejection capability. The proposed FSTP inverter fed IM drive is found quite acceptable considering its performance, cost reduction and other advantages features.
IOSR Journal of Humanities and Social Science is an International Journal edited by International Organization of Scientific Research (IOSR).The Journal provides a common forum where all aspects of humanities and social sciences are presented. IOSR-JHSS publishes original papers, review papers, conceptual framework, analytical and simulation models, case studies, empirical research, technical notes etc.
Proximate, Mineral and Anti-Nutrient Evaluation of Pumpkin Pulp (Cucurbita Pepo)IOSR Journals
Abstract: Proximate, minerals and anti-nutritional concentration of Pumpkin pulp (Cucurbita pepo) were investigated using standard analytical methods as stipulated by AOAC (1990), Agte el al; (1995), Chapman and Pratt, (1961), Kadhakrishna and Sivaprasad (1980), Nelson (1968),Day and underwood, (1986). The proximate composition (%) showed that pumpkin pulp contained Total ash 15.988 ± 0.10, Moisture 0.532 ± 0.10, Fat extract 2.300 ± 0.01 Crude fibre 11.463 ± 0.10, Crude protein 3.070 ± 0.01 and Carbohydrate by difference 66.647 ± 0.01% .The mineral element were Mg, Ca, Mn, Fe, Cu, Pb, Ni and P with values of 189.91 ± 0.2, 179.01 ± 0.2, 0.502 ± 0.1, 1.370 ± 0.1, 3.910 ± 0.1, 0.290 ± 0.1, 0.110 ± o.1 and 11.83 ± 0.2 mg/kg respectively also Na and K with values of 159.01 ± 0.2 and K 160.31 ± 0.1 mg/l00kg were estimated using Flame Emission spectrophotometer. The anti-nutritional analysis of pumpkin pulp gives Phytates 0.618 ± 0.100mgl100kg, Oxalates 16.297 ± 0.100 mg/100kg and Tannins 0.358 ± 0.100 mg/100kg. The results obtained above goes a long way to proof that pumpkin pulp is highly nutritious and at the same time can be used as food formulation for infant due to its nutritional composition.
Key Words: Cucurbita pepo, cucurbitaceae, pumpkin pulp, proximate analysis, mineral
IOSR Journal of Humanities and Social Science is an International Journal edited by International Organization of Scientific Research (IOSR).The Journal provides a common forum where all aspects of humanities and social sciences are presented. IOSR-JHSS publishes original papers, review papers, conceptual framework, analytical and simulation models, case studies, empirical research, technical notes etc.
Voltage profile Improvement Using Static Synchronous Compensator STATCOMINFOGAIN PUBLICATION
Static synchronous compensator (STATCOM) is a regulating device used in AC transmission systems as a source or a sink of reactive power. The most widely utilization of the STATCOM is in enhancing the voltage stability of the transmission line. A voltage regulator is a FACTs device used to adjust the voltage disturbance by injecting a controllable voltage into the system. This paper implement Nruro-Fuzzy controller to control the STATCOM to improve the voltage profile of the power network. The controller has been simulated for some kinds of disturbances and the results show improvements in voltage profile of the system. The performance of STATCOM with its controller was very close within 98% of the nominal value of the busbar voltage.
Voltage profile Improvement Using Static Synchronous Compensator STATCOMINFOGAIN PUBLICATION
Static synchronous compensator (STATCOM) is a regulating device used in AC transmission systems as a source or a sink of reactive power. The most widely utilization of the STATCOM is in enhancing the voltage stability of the transmission line. A voltage regulator is a FACTs device used to adjust the voltage disturbance by injecting a controllable voltage into the system. This paper implement Nruro-Fuzzy controller to control the STATCOM to improve the voltage profile of the power network. The controller has been simulated for some kinds of disturbances and the results show improvements in voltage profile of the system. The performance of STATCOM with its controller was very close within 98% of the nominal value of the busbar voltage.
Digital Implementation of Fuzzy Logic Controller for Real Time Position Contr...IOSR Journals
Abstract: Fuzzy Logic Controller (FLC) systems have emerged as one of the most promising areas for Industrial Applications. The highly growth of fuzzy logic applications led to the need of finding efficient way to hardware implementation. Field Programmable Gate Array (FPGA) is the most important tool for hardware implementation due to low consumption of energy, high speed of operation and large capacity of data storage. In this paper, instead of an introduction to fuzzy logic control methodology, we have demonstrated the implementation of a FLC through the use of the Very high speed integrated circuits Hardware Description Language (VHDL) code. FLC is designed for position control of BLDC Motor. VHDL has been used to develop FLC on FPGA. A Mamdani type FLC structure has been used to obtain the controller output. The controller algorithm developed synthesized, simulated and implemented on FPGA Spartan 3E board. Keywords – BLDC Motor, FLC, Hardware Implementation, Spartan3 FPGA, VHDL
Digital Implementation of Fuzzy Logic Controller for Real Time Position Contr...IOSR Journals
Fuzzy Logic Controller (FLC) systems have emerged as one of the most promising areas for
Industrial Applications. The highly growth of fuzzy logic applications led to the need of finding efficient way to
hardware implementation. Field Programmable Gate Array (FPGA) is the most important tool for hardware
implementation due to low consumption of energy, high speed of operation and large capacity of data storage.
In this paper, instead of an introduction to fuzzy logic control methodology, we have demonstrated the
implementation of a FLC through the use of the Very high speed integrated circuits Hardware Description
Language (VHDL) code. FLC is designed for position control of BLDC Motor. VHDL has been used to develop
FLC on FPGA. A Mamdani type FLC structure has been used to obtain the controller output. The controller
algorithm developed synthesized, simulated and implemented on FPGA Spartan 3E board.
The aim of this paper is to prove that fuzzy logic algorithm is a suitable control technique for fast processes such as electrical machines. This theory has been experimented on different kinds of electrical machines such as stepping motors, dc motors and induction machines (with 6 phases) and the experimental results show that the proposed fuzzy logic algorithm is the most suitable control technique for electrical machines since this algorithm is not time consuming and it is also robust between plant parameters variations.
2.a neuro fuzzy based svpwm technique for pmsm (2)EditorJST
In the present scenario, static frequency converter based variable speed synchronous motors has
become very familiar and advantage to other drive system, especially low speed and high power applications.
Unlike the induction motor, the synchronous motor can be operated at variable power factor (leading, lagging
or unity) as desired. So, there is an increasing use of synchronous motors as adjustable speed drives. The PWM
technique is very useful to VSI drive for achieving efficient and smooth operation and free from torque
pulsations and cogging, lower volume and weight and provides a higher frequency range compared to CSI
drives. Even for voltage source inverter, the commutation circuit is not needed, if the self-extinguishing
switching devices are used. This paper proposes a concept of Neuro-fuzzy based control strategy which is used
for controlling the PMSM. The total work mainly concentrates on optimum control of PMSM with maximum
voltage utilization with less switching losses.
1.a fuzzy based pv apf controller for compensating current harmonics (2)EditorJST
The main aim of this paper is to compensate a current harmonics in PV-APF system using Fuzzy Logic Controller. A 3- Ф 3-wire system is proposed in this paper which consists of PV system, a dc/dc converter which is controlled by MPPT, three phase VSC to act as APF and Non-Linear Load. The main theme of this INC MPPT is to efficiency from the PV system. For reliable performance of active power filter and better harmonic compensation this paper propose a concept of instantaneous power theory. Also, a comparison analysis is performed for improving THD by PI/Fuzzy controllers. The proposed system is simulated and verified in MATLAB/SIMULINK software.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
This paper deals with various power issues such as voltage sag, swell, harmonics, and surges using static synchronous compensator (STATCOM).The conventional controller suffers from uncertain parameters and non-linear qualities. However they are computationally inefficient extending to optimize the fuzzy controller (FC) parameters, since they exhaustively search the optimal values to optimize the objective functions. To overcome this drawback, a genetic algorithm (GA) based Fuzzy controller parameter optimization is presented in this paper. The GA algorithm is used to find the optimal fuzzy parameters for minimizing the objective functions. The feasibility of the proposed GA technique for distribution systems to improve the sag and total harmonic distortion (THD) as major power quality indices in sensitive loads at fault conditions has been simulated and tested. Therefore, the multi-objective optimization algorithm is considered in order to attain a better performance in solving the related problems.
Correlative Study on the Modeling and Control of Boost Converter using Advanc...IJSRD
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FIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdf
J010435966
1. IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE)
e-ISSN: 2278-1676,p-ISSN: 2320-3331, Volume 10, Issue 4 Ver. III (July – Aug. 2015), PP 59-66
www.iosrjournals.org
DOI: 10.9790/1676-10435966 www.iosrjournals.org 59 | Page
Power Quality improvement of Unbalanced Distribution System
Using Fuzzy based D-STATCOM
Kothuri Ramakrishna1,
Dr. Basavaraja Banakara2,
Subramanyam P S3
Abstract: The power quality is a more serious problem for consumers and power companies. In this paper to
mitigate power quality problems such as voltage swell and voltage sag of unbalanced distribution system, a
fuzzy controller based D-STATCOM is proposed. The performance of proposed fuzzy based D-STATCOM is
tested on 13 bus IEEE test feeder, a D-STATCOM is introduced at bus no-632. The performance of proposed
fuzzy based D-STATCOM is compared to D-STATCOM with PI control mechanism using MATLAB-simulink to
address power quality issues.
I. Introduction
Now a day’s power quality is a more serious problem for consumers and power companies. The power
quality issues such as voltage swell and voltage sag leads to economic impact on consumer utility sectors like
induction furnaces and process control of bulk manufactures[1-4].An Electrical distribution system is a
connection between utility sector and Power Company, to provide quality of supply to consumer by maintains
good voltage profile at consumer premises[5].
Causes of Power quality problems in Electrical distribution system [6]
Sag and swell, which varies from 10% to 90% of the rat-ed voltage.
Harmonic distortion in distribution system due to har-monic currents.
Due to lower power factor causes heating of electrical equipment, results heating losses.
It also causes vibration and noise in machines and mal-function of the sensitive equipment.
Due to unbalanced voltages.
There are two methods to resolve power quality problems. The first approach is from source side and
next approach is from load side to diminish well known power quality problems such as voltage swell and
voltage sag.
If there is sudden increase in the load then the voltage in the line decreases rapidly due to the decrease
in the terminal voltage at the receiving end or the utility side. This sudden change in the terminal voltage appears
as sag.
If there is a sudden decrease in the load then the voltage in the line increases rapidly due to the increase
in the terminal voltage at the receiving end or the utility side. This sudden change in the utility side terminal
voltage appears as voltage swell in the line[8].
There are different ways to enhance power quality problems in transmission and distribution systems.
D-STATCOM is a suitable custom power device to address the power quality issues of an unbalanced
distribution system and efficient device to resolve power quality issues, D-STATCOM consisting of a Voltage
Source Converter (VSC) and a shunted DC link capacitor[9-10]. A D-STATCOM is reactive source, generating
and absorbing reactive power. In this paper a 13-bus unbalanced distribution system is considered to address
power quality problem and a D-STATCOM is connected at bus number 632.
Fig.1: Block diagram of D-STATCOM
This paper is organized as follows the D-STATCOM with PI control mechanism is discussed in section
II. The D-STATCOM with fuzzy control mechanism is discussed in section III. In section IV simulation results
are presented where, the performance of D-STATCOM with fuzzy control technique is compared to PI control
2. Power Quality improvement of Unbalanced Distribution System Using Fuzzy based D-STATCOM
DOI: 10.9790/1676-10435966 www.iosrjournals.org 60 | Page
mechanism. Finally conclusions are given in section V.
Fig-2: IEEE-13 bus unbalanced distribution system with D-STATCOM
II. Conventional Control Of D-Statcom
Fig-3:13 Bus unbalanced Distribution System with D-STATCOM with PI Control Mechanism
iii. d-statcom with fuzzy control mechanisam
Fig. 4:13 bus unbalanced distribution system with D-STATCOM with Fuzzy control mechanism
The main objective behind this intelligent controlled strategy is to provide experience to power system
engineer in the implementation of fuzzy controller [12]. The controlled strategy implemented by the engineers
are prepared as set of rules that are simple to carry out manually but difficult to implement by using
conventional control strategy. This approach is a convenient method for constructing nonlinear controllers via
the use of heuristic information.
In this proposed fuzzy controller approach the inputs are error (e) and change in error (∆e) generates
required control signal.
The design procedure of FLC consists of the following modules: 1) Fuzzification 2) Fuzzy Rule- base
3) Fuzzy Inference Engine (Decision Making Logic) and 4) Defuzzification.
A Fuzzy controller operates by repeating a cycle of following four steps. First, measurements are taken
of all variables that represent relevant conditions of the controlled
3. Power Quality improvement of Unbalanced Distribution System Using Fuzzy based D-STATCOM
DOI: 10.9790/1676-10435966 www.iosrjournals.org 61 | Page
process (Universal Discourse). Next, these measurements are converted into appropriate fuzzy sets to express
measurement uncertainties (Fuzzification). The fuzzified measurements are the used by the inference engine
(Decision Making Logic) to evaluate the control rules stored in fuzzy rule base . The result of this evaluation is a
output fuzzy set (or several fuzzy sets) defined on the universe of possible actions and the degree of membership
of the output fuzzy set can be calculated by using Root Sum Square Method. This fuzzy set is then converted, in
the final step of the cycle, into a crisp (single) value that, in some sense, is the best representative of the fuzzy
set (Defuzzification). The defuzzified value represents the actions taken by the fuzzy controller in individual
control cycles. Now, in the following Sections we develop the various components of FLC to solve power
quality problem. Fuzzy controller is developed to generate required control signal it receives the input signal
from the system and processing the data in different stages and generate required output.
Fig-5: Input and output of FLC controller
Selection of inputs and outputs:
In the design of fuzzy controller to address power quality problem the input variables selected as error
(e) and change in error (delta e). It takes fuzzy input from fuzzifier in form of membership value matrix and uses
fuzzy rule base to decide the fuzzy value of output. The control signal which represents rule base in terms of
membership function. The upper limit and the lower limit of the error, change in error is specified on the
previous experience of power system engineer.
Fuzzification:
Fuzzification is a process of converting crisp value of input data into suitable linguistic values through
membership function [12].
Development of fuzzy decision rules
The construction of rule base involves [12]:
Based on the Expert Experience and Control Engi-neering Knowledge the rules are formed in the form
of “if-then ” and for the present two inputs –One output case, and for two number fuzzy input parti-tions, the
maximum number 3*3=9 rules are to be formed.
After forming all the rules they will be tabulated in the Decision Table.
Fuzzy decision rules developed based on previous experience of power system engineer a set of control
rules can be developed these set of rules are vary person to person depends on personal experience in any
particular field. There are two fuzzy variables for each input variable; therefore 4 decision rules are possible.
This decision table consisting of
linguistic numeric consequents of the rules. The number of rules depends on number of input variables, here we
considered input variables are three so maximum of 9 rules can be possible. For example
1. If “error” is negative and “change in error” is negative than output is negative.
2. If “error” is negative and “change in error” is zero than output is negative.
3. If “error” is negative and “change in error” is positive than output is zero.
4. If “error” is zero and “change in error” is nega-tive than output is negative.
5. 5. .If “error” is zero and “change in error” is zero than output is zero.
6. If “error” is zero and “change in error” is posi-tive than output is positive.
7. If “error” is positive and “change in error” is
negative than output is zero.
8. If “error” is positive and “change in error” is zero than output is positive.
9. If “error” is positive and “change in error” is positive than output is positive.
4. Power Quality improvement of Unbalanced Distribution System Using Fuzzy based D-STATCOM
DOI: 10.9790/1676-10435966 www.iosrjournals.org 62 | Page
N - Negative, P - Positive, Z – Zero
Fig. – 6: Decision rules for the implementation of FLC controller
Fuzzy inference system
Fuzzy inference is the process of mapping from a given input to output using fuzzy logic. There are two
types of fuzzy inference systems that can be implemented using fuzzy logic. There are two fuzzy inference
systems for implementation of fuzzy logic one is mamdani type and sugeno type these two types of inference
system differs somewhat in the way output are determined.
Aggregation of fuzzy rule:
The fuzzy rule based system may contain more than one rule. the process of formulating overall
conclusions from the individually specified consequents contributed by each rule the fuzzy rule is known as
aggregation of the rule(or) computation of IF part of the rule is called aggregation(or)calculation of IF part of the
rule is called aggregation.
Composition:
Calculation of THEN part of the rules is called composition.
Aggregation:
To represent in logical convenience new logical operators AND, OR, NOT are widely used in most of
fuzzy logic applications
Composition:
Each rule defines an action has to be taken in THEN
part.
The degree which action is valid is given by the satisfactory of rules. This satisfactory is calculated by
aggregation as degree of IF part.
Decision table: The above 9 rules become the entries of decision table and are shown in shown in
below.
III. Algorithm For Design Of Flc
The following algorithm is proposed for designing of Fuzzy logic controller to mitigate power quality
problem of four bus system.
Step 1: Select the input variables to enhance power quality issues like swell, sag. error and change in error are
selected as fuzzy inputs and the output of the FLC is proposed as the phase angle of injected current(D-
STATCOM)
Step 2: Selected input and out variables are then partitioned in to 2 regions and their membership functions have
been defined.
Step 3: With the knowledge of the power quality issue like voltage swell and voltage sag (through the method,
“Expert Experience and Control Engineering Knowl-edge”), 9 rules are framed to decide the
membership function value of the output variable. The rules are then tabulated in the Decision-Table.
Step 4: Fuzzy output sets are formed and the strengths of each of the output membership function is estimated by
Root Mean Square method.
Step 5: By applying defuzzification, Crisp output is obtained. Step 6: With the crisp value, output signal is
generated.
IV. Simulation Results
In this work a D-STATCOM with fuzzy control mechanism have been proposed to improve power
quality (voltage swell, voltage sag) of 13-bus IEEE distribution system. Simulations are performed using
5. Power Quality improvement of Unbalanced Distribution System Using Fuzzy based D-STATCOM
DOI: 10.9790/1676-10435966 www.iosrjournals.org 63 | Page
MATLAB SIMULINK.The performance of proposed D-STATCOM with fuzzy logic control technique is
compared to D-STATCOM with PI control technique.
Fig-7: Illustrates the Voltage sag mitigation from source side using D-STATCOM with PI & fuzzy control
Fig-8: Illustrates Voltages swell mitigation from source side using D-STATCOM with PI & fuzzy control
6. Power Quality improvement of Unbalanced Distribution System Using Fuzzy based D-STATCOM
DOI: 10.9790/1676-10435966 www.iosrjournals.org 64 | Page
Fig-9: Illustrates the Voltage sag mitigation from load side using D-STATCOM with PI & fuzzy control
Fig-10: Illustrates Voltages swell mitigation from load side using D-STATCOM with PI & fuzzy control.
V. Conclusion
In this paper for enhancement of power quality of distribution system a 13- bus unbalanced distribution
system is considered. A fuzzy control based D-STATCOM is introduced at bus number-632 of 13-buses IEEE
test feeder system. The performance of proposed method is compared with PI based D-STATCOM. Simulation
results revealed that the proposed model free intelligent control(fuzzy) methodology based D-STATCOM tackle
7. Power Quality improvement of Unbalanced Distribution System Using Fuzzy based D-STATCOM
DOI: 10.9790/1676-10435966 www.iosrjournals.org 65 | Page
power quality issues such as voltage sag, voltage swell at all bus considerable by introducing fuzzy controller
based D-STATCOM at bus no 632.The fuzzy based D-STATCOM is quite capable of suppressing voltage swell
and voltage sag compared to PI based D-STATCOM.
References
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Publication Year: 2001 , Page(s): 1132 - 1137 vol.2.
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Biographies
Kothuri Ramakrishna completed his Bachelor of Engineering (B.E.) from Gulbarga University in the year
1998 and Master of Technology (M.Tech.) from J.N.T.U Hyderabad in 2001. He also completed Master of
Business Administration (MBA) from Annamalai University in 2013. Presently, he is pursuing Ph.D from
J.N.T.U.
Hyderabad. Right now, he has around 16 years of teaching experience. His research interest includes Power
Electronics, Power Quality, Power System Analysis, Power System Dynamics, etc.
8. Power Quality improvement of Unbalanced Distribution System Using Fuzzy based D-STATCOM
DOI: 10.9790/1676-10435966 www.iosrjournals.org 66 | Page
Dr. Basavaraja Banakara BE, ME, MBA (HR),
PhD (NITW), Senior Member EEE, LMISTE,. He obtained his Doctoral degree from National Institute of
Technology, Warangal, India. He is having 20 years teaching experience in engineering college at Lecturer,
Associate Professor, and Professor, & Principal level. Presently he is working as Professor & HOD,
Department of Electrical and Electronics Engineering, University of BDT Engineering College (Constituent
College of Visvesvaraya Technological University), Davanagere, Karnataka, India. His areas of interest include
power electronics and drives, Utilization of Electrical Engineering, High voltage Engineering and EMTP
applications. Presented 30 publications in national & international journals as well as in conferences.
Subramanyam P S received his bachelor of Engineering in Electrical & Electronics Engineering from Andhra
University in the year 1960 & Master’s Degree in Electrical Power Systems from Jawaharlal Nehru
Technological University, Anantapur in the year 1977. He received his PhD from IIT Madras in the year 1983.
He published a number of papers in National and International
Journals, Conferences, and several text books. Basically from Electrical Engineering discipline, he migrated to
the field of Computer Science and Engineering. His areas of interest include Fault analysis, six-phase system
and six-phase induction motors.