Stator current drift compensation of induction motor based on RBF neural network is proposed here. In vector control of induction motor decoupling of speed and rotor flux equations and their simultaneous control are used to achieve the highest efficiency and fast dynamic
performance. The highest efficiency is reached when the proper flux is selected and as a result of dynamic decoupling of speed and rotor flux equations, the rotor flux can be modified to achieve the highest efficiency and make the speed be at its desired value. The precise control of these changes can also be done using radial basis function neural network (RBFNN). Once
neural network gets trained then it is able to differentiate between normal and fault conditions and therefore acts in accordance to the change that could bring back the system to normal condition. Here, neural network is used to compute the appropriate set of voltage and frequency
to achieve the maximum efficiency for any value of operating torque and motor speed.
Direct Torque Control (DTC) of Induction Motor drive has quick torque response without complex orientation transformation and inner loop current control. DTC has some drawbacks, such as the torque and flux ripple. The control scheme performance relies on the accurate selection of the switching voltage vector. This proposed simple structured neural network based new identification method for flux position estimation, sector selection and stator voltage vector selection for induction motors using direct torque control (DTC) method. The ANN based speed controller has been introduced to achieve good dynamic performance of induction motor drive. The Levenberg-Marquardt back-propagation technique has been used to train the neural network. Proposed simple structured network facilitates a short training and processing times. The stator flux is estimated by using the modified integration with amplitude limiter algorithms to overcome drawbacks of pure integrator. The conventional flux position estimator, sector selector and stator voltage vector selector based modified direct torque control (MDTC) scheme compared with the proposed scheme and the results are validated through both by simulation and experimentation.
Indirect Vector Control of Induction Motor Using Pi Speed Controller and Neur...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Simulation of Direct Torque Control of Induction motor using Space Vector Mo...IJMER
This paper presents simulation of Direct Torque Control (DTC) of Induction Motor using Space
Vector Modulation (SVM). Direct Torque Control is a control strategy used for high performance torque
control of Induction Motor. This SVM based DTC technique reduces torque ripple and improves torque
response. The performance is explained using simulation in MATLAB environment. Result of the
simulation done in the paper shows improvement in flux and torque. These results verifies the merits of
DTC- SVM over conventional Direct Torque Control technique.
Speed Control System of Induction Motor by using Direct Torque Control Method...ijtsrd
Escalator is useful and act in the important part to carry passengers to the targeted floors of building. Every escalator must be driven by its own motor and this motor speed must be controled. To drive escalator with a constant speed, direct torque control technique is used to drive three phase squirrel cage induction motor. In this paper, the development of speed control system for three phase squirrel cage induction motor using a direct torque control method is presented and simulation for proposed system is done with the help of MATLAB SIMULINK. Soe Sandar Aung | Thet Naing Htun "Speed Control System of Induction Motor by using Direct Torque Control Method used in Escalator" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27903.pdfPaper URL: https://www.ijtsrd.com/engineering/electrical-engineering/27903/speed-control-system-of-induction-motor-by-using-direct-torque-control-method-used-in-escalator/soe-sandar-aung
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
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.
Direct Torque Control (DTC) of Induction Motor drive has quick torque response without complex orientation transformation and inner loop current control. DTC has some drawbacks, such as the torque and flux ripple. The control scheme performance relies on the accurate selection of the switching voltage vector. This proposed simple structured neural network based new identification method for flux position estimation, sector selection and stator voltage vector selection for induction motors using direct torque control (DTC) method. The ANN based speed controller has been introduced to achieve good dynamic performance of induction motor drive. The Levenberg-Marquardt back-propagation technique has been used to train the neural network. Proposed simple structured network facilitates a short training and processing times. The stator flux is estimated by using the modified integration with amplitude limiter algorithms to overcome drawbacks of pure integrator. The conventional flux position estimator, sector selector and stator voltage vector selector based modified direct torque control (MDTC) scheme compared with the proposed scheme and the results are validated through both by simulation and experimentation.
Indirect Vector Control of Induction Motor Using Pi Speed Controller and Neur...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Simulation of Direct Torque Control of Induction motor using Space Vector Mo...IJMER
This paper presents simulation of Direct Torque Control (DTC) of Induction Motor using Space
Vector Modulation (SVM). Direct Torque Control is a control strategy used for high performance torque
control of Induction Motor. This SVM based DTC technique reduces torque ripple and improves torque
response. The performance is explained using simulation in MATLAB environment. Result of the
simulation done in the paper shows improvement in flux and torque. These results verifies the merits of
DTC- SVM over conventional Direct Torque Control technique.
Speed Control System of Induction Motor by using Direct Torque Control Method...ijtsrd
Escalator is useful and act in the important part to carry passengers to the targeted floors of building. Every escalator must be driven by its own motor and this motor speed must be controled. To drive escalator with a constant speed, direct torque control technique is used to drive three phase squirrel cage induction motor. In this paper, the development of speed control system for three phase squirrel cage induction motor using a direct torque control method is presented and simulation for proposed system is done with the help of MATLAB SIMULINK. Soe Sandar Aung | Thet Naing Htun "Speed Control System of Induction Motor by using Direct Torque Control Method used in Escalator" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27903.pdfPaper URL: https://www.ijtsrd.com/engineering/electrical-engineering/27903/speed-control-system-of-induction-motor-by-using-direct-torque-control-method-used-in-escalator/soe-sandar-aung
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
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.
OPTIMAL TORQUE RIPPLE CONTROL OF ASYNCHRONOUS DRIVE USING INTELLIGENT CONTROL...elelijjournal
The dynamic performance of an asynchronous machine when operated with cascaded Voltage Source Inverter using Space Vector Modulation (SVM) technique is presented in this paper. A classical model of Induction Motor Drive based on Direct Torque Control (DTC) method is considered which displays
appreciable run-time operation with very simple hysteresis control scheme. Direct control of the torque and flux variables is achieved by choosing suitable inverter voltage space vector from a lookup table. Under varying torque conditions the performance of the drive system is verified using MATLAB/Simulink software tool. The ripple content in the torque parameter is significant when traditional PI controller and Fuzzy approach are configured in the proposed system. Finally, by replacing the PI-Fuzzy controller with Hybrid Controller the torque ripple minimization can be achieved during no-load and loaded conditions.
TORQUE CONTROL OF AC MOTOR WITH FOPID CONTROLLER BASED ON FUZZY NEURAL ALGORITHMijics
Nowadays in the complicated systems, design of proper and implementable controller has a most importance. With respect to ability of fractional order systems in complicated systems identification as a first order fractional system with time delay, usage of fractional order PID has a proper result. From one side flexibility of fractional calculus than integer order has been topics of interest to the researchers. From another side, PMSM motors which are one the AC motor types, has been allocated largely accounted position in industry and used in variety applications. Therefore in this paper torque direct control of PMSM motors with FOPID based on model is proposed. Also fuzzy neural controllers are widely considered. Reason of this is success of fuzzy neural controller in control and identification of uncertain and complicated systems. The proposed method in this paper is combination of FOPID controller with fuzzy neural supervision system which with coefficients setting of this controller, control operation of PMSM will improve. Results of proposed method show the ability of proposed technique in reference signal tracking, elimination of disturbances effects and functional robustness in presence of noise and uncertainty. The results show the error averagely in three condition, nominal form, step disturbance and noise and uncertainly will decrease 11.66% in proposed method (FNFOPID) with Integral Square Error criterion and 7.69% with Integral Absolute Error criterion in comparison to FOPID.
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.
Power optimisation scheme of induction motor using FLC for electric vehicleAsoka Technologies
In electric vehicles (EVs) and hybrid EVs, energy efficiency is essential where the energy storage is limited. Adding to its high stability and low cost, the induction motor efficiency improves with loss minimisation. Also, it can consume more power than the actual need to perform its working when it is operating in less than full load condition. This study proposes a control strategy based on the fuzzy logic control (FLC) for EV applications. FLC controller can improve the starting current amplitude and saves more power. Through the MATLAB/SIMULINK software package, the performance of this control was verified through simulation. As compared with the conventional proportional integral derivative controller, the simulation schemes show good, high-performance results in time-domain response and rapid rejection of system-affected disturbance. Therefore, the core losses of the induction motor are greatly reduced, and in this way improves the efficiency of the driving system. Finally, the suggested control system is validated by the experimental results obtained in the authors’ laboratory, which are in good agreement with the simulation results.
Speed Control of Induction Motor using FOC MethodIJERA Editor
An increasing number of applications in high performing electrical drive systems use nowadays, squirrel-cage induction motors. This paper describes a simplified method for the speed control of a three phase AC drive using Proportional-Integral controller. The simulation results show that the step response of the model is very fast, steady and able to work in four quadrants, and robustness and high performance is achieved.
Fuzzy controlled dtc fed by a four switch inverter for induction motoreSAT Journals
Abstract
Direct Torque Control of induction motor fed drives has become popular and widely used in industries due to fast and good
torque response. Induction motors (IM) are simple in construction and are less sensitive to the motor parameters compared to
other vector control methods. The conventional DTC is based on flux and torque hysteresis controllers. Induction motor is fed
from a Four Switch Inverter generating the voltage vectors of the Six Switch Inverter by reconfiguration. Applying the most
optimized voltage vector that produce fastest dynamic torque response during transient states. Fuzzy logic concept is a most
efficient artificial integilence method which has high application in electric motor drives. A method to achieve fastest dynamic
performance by modifying the two leg inverter fed DTC of induction motor based on Fuzzy Logic Concept is used here. This paper
presents a rule-based fuzzy logic controller scheme designed and applied for the speed control of an induction motor fed from a
four switch three phase inverter emulating the six switch three phase inverter. Due to the usage of the Fuzzy logic concept, the
reliability, efficiency and performance of ac drive increases. Initial torque peak and torque ripple are minimized in the four switch
three phase inverter based DTC using Fuzzy Logic.
Key Words: Direct Torque Control , Four Switch/Six Switch Three Phase Inverter, Fuzzy Logic, Induction motor(IM).
Speed control of sensorless brushless DC motor by computing back EMF from lin...IJAAS Team
Sensorless operation of permanent magnet brushless direct current (BLDC) motor drive controls the rotating speed with different applied voltage. No phase lagging is produced which leads to increase the efficiency and minimize the torque pulsation of the BLDC motor. Initially, motor can be started by following the v/f method then allows the sensorless mode after reaching the minimum speed of 500-1000rpm. The Sensorless BLDC motors are highly used due to higher efficiency, reliability power, acoustic noise, smaller, lighter, greater dynamic response, better speed versus torque characteristics, higher speed range and longer life. Thus, the source voltage spikes and switching losses are reduced. This method can be demonstrated through MATLAB simulation and DSP TMS 320LF2407A is used in the experimental setup to get the output.
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.
Speed Sensorless Vector Control of Induction Motor Drive with PI and Fuzzy Co...IJPEDS-IAES
This paper directed the speed-sensorless vector control of induction motor drive with PI and fuzzy controllers. Natural observer with fourth order state space model is employed to estimate the speed and rotor fluxes of the induction motor. The formation of the natural observer is similar to and as well as its attribute is identical to the induction motor. Load torque adaptation is provided to estimate the torque and rotor speed is estimated from the load torque, rotor fluxes and stator currents. There is no direct feedback in natural observer and also observer gain matrix is absent. Both the induction motor and the observer are characterized by state space model. Simple fuzzy logic controller and conventional PI controllers are used to control the speed of the induction motor in closed loop. MATLAB simulations are made with PI and fuzzy controllers and the performance of fuzzy controller is better than PI controller in view of torque ripples. The simulation results are obtained for various running conditions to exhibit the suitability of this method for sensorless vector control. Experimental results are provided for natual observer based sensorless vector control with conventional PI controller.
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.
DC MOTOR SPEED CONTROL USING ON-OFF CONTROLLER BY PIC16F877A MICROCONTROLLERTridib Bose
This presentation consists the speed control of a dc motor using hardware (microcontroller) by changing the reference voltages logically and minimising errors.
Analysis of Direct Torque Control of Industrial Drives using Zone-Shifting SVMIJPEDS-IAES
Direct Torque Control of Induction Motor has gained popularity in industrial applications mainly due to its simple control structure from its first introduction in 1986. Here the direct torque control (DTC) of induction motor with zone shifting space vector modulation (SVM) has been done. It uses a simple phase current re-construction algorithm for three phase induction motor (IM). The phase current re-construction algorithm is done by using information from the current that is from the phases between the inverter and the induction motor. The proposed algorithm is robust and very simple. It uses the AC current to get the stator current for estimating the motor flux and the electromagnetic torque. By evaluating through the torque value and the current the controlling of induction motor is done. The simulation results are also given which supports the direct torque control strategy of the induction motor (IM).
Direct Torque Control (DTC) is widely applied for ac motor drives as it offers high performance torque control with a simple control strategy. However, conventional DTC poses some disadvantages especially in term of variable switching frequency and large torque ripple due to the utilization of torque hysteresis controller. Other than that, performance of conventional DTC fed by two-level inverter is also restricted by the limited numbers of voltage vectors which lead to inappropriate selection of voltage vectors for different speed operations. This research aims to propose a Constant Switching Frequency (CSF) torque controller for DTC of induction motor (IM) fed by three-level Neutral-Point Clamped (NPC) inverter. The proposed torque controller utilizes PI controller which apply different gain for different speed operation. Besides, the utilization of NPC inverter provides greater number of voltage vectors which allow appropriate selection of voltage vectors for different operating condition. Using the proposed method, the improvement of DTC drives in term of producing a constant switching operation and minimizing torque ripple are achieved and validated via experimental results.
Field oriented control and direct torque control are the most popular methods in high
performance industrial control applications for induction motors. Naturally, the strengths and
weaknesses of each control method are available. Therefore, the selection of optimum control
method is vitally important for many industrial applications. So, the advantages and the
disadvantages of both control methods have to be well defined. In this paper, a new and
different perspective has been presented regarding the comparison of the inverter switching
behaviours on the FOC and the DTC drivers. For this purpose, the experimental studies have
been carried out to compare the inverter switching frequencies and torque responses of
induction motors in the FOC and the DTC systems. The dSPACE 1103 controller board has
been programmed with Matlab/Simulink software. As expected, the experimental studies have
showed that the FOC controlled motors have had a lessened torque ripple. On the other hand,
the FOC controlled motor switching frequency has about 75% more than the DTC controlled.
ADAPTIVE BANDWIDTH APPROACH ON DTC CONTROLLED INDUCTION MOTORijics
Induction motors are most commonly used motor type in industrial applications because of its well-known
advantages like robust structure, cheaper prices etc. Today, field oriented control (FOC) and direct torque
control (DTC) methods, also called vector control, are most famous control methods in high-performance
applications. The main structural and behavioural differences between the both methods can be
summarized as: the FOC has parameter dependence while the DTC has high torque ripples. In this study, a
new adaptive bandwidth approach was presented to reduce torque ripples in DTC controlled induction
motor drives. With the proposed method, instead of fixed bandwidth, adaptive bandwidth approach was
investigated in hysteresis controllers on the DTC method. Both the conventional DTC(C-DTC) method and
adaptive bandwidth DTC (AB-DTC) for induction motor were simulated in MATLAB/SIMULINK and the
results were presented and discussed to verify the proposed control. The comparisons shown that, torque
ripples were reduced remarkably with the proposed AB-DTC method.
OPTIMAL TORQUE RIPPLE CONTROL OF ASYNCHRONOUS DRIVE USING INTELLIGENT CONTROL...elelijjournal
The dynamic performance of an asynchronous machine when operated with cascaded Voltage Source Inverter using Space Vector Modulation (SVM) technique is presented in this paper. A classical model of Induction Motor Drive based on Direct Torque Control (DTC) method is considered which displays
appreciable run-time operation with very simple hysteresis control scheme. Direct control of the torque and flux variables is achieved by choosing suitable inverter voltage space vector from a lookup table. Under varying torque conditions the performance of the drive system is verified using MATLAB/Simulink software tool. The ripple content in the torque parameter is significant when traditional PI controller and Fuzzy approach are configured in the proposed system. Finally, by replacing the PI-Fuzzy controller with Hybrid Controller the torque ripple minimization can be achieved during no-load and loaded conditions.
TORQUE CONTROL OF AC MOTOR WITH FOPID CONTROLLER BASED ON FUZZY NEURAL ALGORITHMijics
Nowadays in the complicated systems, design of proper and implementable controller has a most importance. With respect to ability of fractional order systems in complicated systems identification as a first order fractional system with time delay, usage of fractional order PID has a proper result. From one side flexibility of fractional calculus than integer order has been topics of interest to the researchers. From another side, PMSM motors which are one the AC motor types, has been allocated largely accounted position in industry and used in variety applications. Therefore in this paper torque direct control of PMSM motors with FOPID based on model is proposed. Also fuzzy neural controllers are widely considered. Reason of this is success of fuzzy neural controller in control and identification of uncertain and complicated systems. The proposed method in this paper is combination of FOPID controller with fuzzy neural supervision system which with coefficients setting of this controller, control operation of PMSM will improve. Results of proposed method show the ability of proposed technique in reference signal tracking, elimination of disturbances effects and functional robustness in presence of noise and uncertainty. The results show the error averagely in three condition, nominal form, step disturbance and noise and uncertainly will decrease 11.66% in proposed method (FNFOPID) with Integral Square Error criterion and 7.69% with Integral Absolute Error criterion in comparison to FOPID.
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.
Power optimisation scheme of induction motor using FLC for electric vehicleAsoka Technologies
In electric vehicles (EVs) and hybrid EVs, energy efficiency is essential where the energy storage is limited. Adding to its high stability and low cost, the induction motor efficiency improves with loss minimisation. Also, it can consume more power than the actual need to perform its working when it is operating in less than full load condition. This study proposes a control strategy based on the fuzzy logic control (FLC) for EV applications. FLC controller can improve the starting current amplitude and saves more power. Through the MATLAB/SIMULINK software package, the performance of this control was verified through simulation. As compared with the conventional proportional integral derivative controller, the simulation schemes show good, high-performance results in time-domain response and rapid rejection of system-affected disturbance. Therefore, the core losses of the induction motor are greatly reduced, and in this way improves the efficiency of the driving system. Finally, the suggested control system is validated by the experimental results obtained in the authors’ laboratory, which are in good agreement with the simulation results.
Speed Control of Induction Motor using FOC MethodIJERA Editor
An increasing number of applications in high performing electrical drive systems use nowadays, squirrel-cage induction motors. This paper describes a simplified method for the speed control of a three phase AC drive using Proportional-Integral controller. The simulation results show that the step response of the model is very fast, steady and able to work in four quadrants, and robustness and high performance is achieved.
Fuzzy controlled dtc fed by a four switch inverter for induction motoreSAT Journals
Abstract
Direct Torque Control of induction motor fed drives has become popular and widely used in industries due to fast and good
torque response. Induction motors (IM) are simple in construction and are less sensitive to the motor parameters compared to
other vector control methods. The conventional DTC is based on flux and torque hysteresis controllers. Induction motor is fed
from a Four Switch Inverter generating the voltage vectors of the Six Switch Inverter by reconfiguration. Applying the most
optimized voltage vector that produce fastest dynamic torque response during transient states. Fuzzy logic concept is a most
efficient artificial integilence method which has high application in electric motor drives. A method to achieve fastest dynamic
performance by modifying the two leg inverter fed DTC of induction motor based on Fuzzy Logic Concept is used here. This paper
presents a rule-based fuzzy logic controller scheme designed and applied for the speed control of an induction motor fed from a
four switch three phase inverter emulating the six switch three phase inverter. Due to the usage of the Fuzzy logic concept, the
reliability, efficiency and performance of ac drive increases. Initial torque peak and torque ripple are minimized in the four switch
three phase inverter based DTC using Fuzzy Logic.
Key Words: Direct Torque Control , Four Switch/Six Switch Three Phase Inverter, Fuzzy Logic, Induction motor(IM).
Speed control of sensorless brushless DC motor by computing back EMF from lin...IJAAS Team
Sensorless operation of permanent magnet brushless direct current (BLDC) motor drive controls the rotating speed with different applied voltage. No phase lagging is produced which leads to increase the efficiency and minimize the torque pulsation of the BLDC motor. Initially, motor can be started by following the v/f method then allows the sensorless mode after reaching the minimum speed of 500-1000rpm. The Sensorless BLDC motors are highly used due to higher efficiency, reliability power, acoustic noise, smaller, lighter, greater dynamic response, better speed versus torque characteristics, higher speed range and longer life. Thus, the source voltage spikes and switching losses are reduced. This method can be demonstrated through MATLAB simulation and DSP TMS 320LF2407A is used in the experimental setup to get the output.
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.
Speed Sensorless Vector Control of Induction Motor Drive with PI and Fuzzy Co...IJPEDS-IAES
This paper directed the speed-sensorless vector control of induction motor drive with PI and fuzzy controllers. Natural observer with fourth order state space model is employed to estimate the speed and rotor fluxes of the induction motor. The formation of the natural observer is similar to and as well as its attribute is identical to the induction motor. Load torque adaptation is provided to estimate the torque and rotor speed is estimated from the load torque, rotor fluxes and stator currents. There is no direct feedback in natural observer and also observer gain matrix is absent. Both the induction motor and the observer are characterized by state space model. Simple fuzzy logic controller and conventional PI controllers are used to control the speed of the induction motor in closed loop. MATLAB simulations are made with PI and fuzzy controllers and the performance of fuzzy controller is better than PI controller in view of torque ripples. The simulation results are obtained for various running conditions to exhibit the suitability of this method for sensorless vector control. Experimental results are provided for natual observer based sensorless vector control with conventional PI controller.
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.
DC MOTOR SPEED CONTROL USING ON-OFF CONTROLLER BY PIC16F877A MICROCONTROLLERTridib Bose
This presentation consists the speed control of a dc motor using hardware (microcontroller) by changing the reference voltages logically and minimising errors.
Analysis of Direct Torque Control of Industrial Drives using Zone-Shifting SVMIJPEDS-IAES
Direct Torque Control of Induction Motor has gained popularity in industrial applications mainly due to its simple control structure from its first introduction in 1986. Here the direct torque control (DTC) of induction motor with zone shifting space vector modulation (SVM) has been done. It uses a simple phase current re-construction algorithm for three phase induction motor (IM). The phase current re-construction algorithm is done by using information from the current that is from the phases between the inverter and the induction motor. The proposed algorithm is robust and very simple. It uses the AC current to get the stator current for estimating the motor flux and the electromagnetic torque. By evaluating through the torque value and the current the controlling of induction motor is done. The simulation results are also given which supports the direct torque control strategy of the induction motor (IM).
Direct Torque Control (DTC) is widely applied for ac motor drives as it offers high performance torque control with a simple control strategy. However, conventional DTC poses some disadvantages especially in term of variable switching frequency and large torque ripple due to the utilization of torque hysteresis controller. Other than that, performance of conventional DTC fed by two-level inverter is also restricted by the limited numbers of voltage vectors which lead to inappropriate selection of voltage vectors for different speed operations. This research aims to propose a Constant Switching Frequency (CSF) torque controller for DTC of induction motor (IM) fed by three-level Neutral-Point Clamped (NPC) inverter. The proposed torque controller utilizes PI controller which apply different gain for different speed operation. Besides, the utilization of NPC inverter provides greater number of voltage vectors which allow appropriate selection of voltage vectors for different operating condition. Using the proposed method, the improvement of DTC drives in term of producing a constant switching operation and minimizing torque ripple are achieved and validated via experimental results.
Field oriented control and direct torque control are the most popular methods in high
performance industrial control applications for induction motors. Naturally, the strengths and
weaknesses of each control method are available. Therefore, the selection of optimum control
method is vitally important for many industrial applications. So, the advantages and the
disadvantages of both control methods have to be well defined. In this paper, a new and
different perspective has been presented regarding the comparison of the inverter switching
behaviours on the FOC and the DTC drivers. For this purpose, the experimental studies have
been carried out to compare the inverter switching frequencies and torque responses of
induction motors in the FOC and the DTC systems. The dSPACE 1103 controller board has
been programmed with Matlab/Simulink software. As expected, the experimental studies have
showed that the FOC controlled motors have had a lessened torque ripple. On the other hand,
the FOC controlled motor switching frequency has about 75% more than the DTC controlled.
ADAPTIVE BANDWIDTH APPROACH ON DTC CONTROLLED INDUCTION MOTORijics
Induction motors are most commonly used motor type in industrial applications because of its well-known
advantages like robust structure, cheaper prices etc. Today, field oriented control (FOC) and direct torque
control (DTC) methods, also called vector control, are most famous control methods in high-performance
applications. The main structural and behavioural differences between the both methods can be
summarized as: the FOC has parameter dependence while the DTC has high torque ripples. In this study, a
new adaptive bandwidth approach was presented to reduce torque ripples in DTC controlled induction
motor drives. With the proposed method, instead of fixed bandwidth, adaptive bandwidth approach was
investigated in hysteresis controllers on the DTC method. Both the conventional DTC(C-DTC) method and
adaptive bandwidth DTC (AB-DTC) for induction motor were simulated in MATLAB/SIMULINK and the
results were presented and discussed to verify the proposed control. The comparisons shown that, torque
ripples were reduced remarkably with the proposed AB-DTC method.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Mathematical Modelling of an 3 Phase Induction Motor Using MATLAB/Simulink IJMER
Mechanical energy is needed in the daily life use as well as in the industry. Induction motors
play a very important role in both worlds, because of low cost, reliable operation, robust operation and low
maintenance. To derive the mathematical model of a 3 phase Induction motor, the theory of reference
frames has been effectively used as an efficient approach. Dynamic models (mathematical models) are
employed in to better understand the behaviour of induction motor in both transient and steady state. The
dynamic modelling sets all the mechanical equations for the inertia, torque and speed versus time. It also
models all the differential voltage, currents and flux linkages between the stationary stator as well as the
moving rotor. This paper presents a step by step Matlab/Simulink implementation of an induction machine
using dq0 axis transformations of the stator and rotor variables in the arbitrary reference frame [1].
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.
Fuzzy-Logic-Controller-Based Fault Isolation in PWM VSI for Vector Controlled...iosrjce
IOSR Journal of Electrical and Electronics Engineering(IOSR-JEEE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of electrical and electronics engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electrical and electronics engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
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.
Dual inverter fed induction motor drives provide more advantages in contrast with other multilevel inverter drives. Coupled PWM techniques provide good standard of output voltage than the decoupled PWM techniques for dual inverter configuration. In this paper analysis of open end winding induction motor by coupled random PWM signals and decoupled SVPWM signals was carried out. Induction motor by random PWM technique generate low acoustic noise and electromagnetic interference to near by systems. The performance evaluation of the drive wss implemented in MATLAB/simulink and the results were presented.
Induction motor harmonic reduction using space vector modulation algorithmjournalBEEI
The vector control was proposed as an alternative to the scalar control for AC machines control. Vector control provide high operation performance in steady state and transient operation. However, the variable switching frequency of vector control causes high flux and torque ripples which lead to an acoustical noise and degrade the performance of the control scheme. The insertion of the space vector modulation was a very useful solution to reduce the high ripples level inspite of its complexity. Numerical simulation results obtained in MATLAB/Simulink show the good dynamic performance of the proposed vector control technique and the effectiveness of the proposed sensorless strategy in the presence of the sudden load torque basing on the integral backstepping approach capabilities on instant perturbation rejection.
Keywords
In this paper, DTC is applied for two-level inverter fed IM drives based on neuronal hysteresis comparators and The Direct Torque Control (DTC) is known to produce quick and robust response in AC drive system. However, during steady state, torque, flux and current ripple. An improvement of electric drive system can be obtained using a DTC method based on ANNs which reduces the torque and flux ripples, the estimated the rotor speed using the KUBOTA observer method based on measurements of electrical quantities of the motor. The validity of the proposed methods is confirmed by the simulation results.The THD (Total Harmonic Distortion) of stator current, torque ripple and stator flux ripple are determined and compared with conventional DTC control scheme using Matlab/Simulink environment.
Advance Current Monitoring Techniques to Detect and Diagnosis the Inter-Turn ...theijes
This paper presents the results of stator inter-turn fault detection and diagnosis in three phase induction motor using different types of current monitoring techniques such as: motor current signature analysis (MCSA), Current Concordia Vector, extend park vector approach (EPVA). Where the use of several signal processing techniques for extracting more information about the fault, will help us knowing the characteristics of each method in order to choose the best way to diagnose this type of machine fault. The tests show that the EPVA technique can diagnose the inter-turn fault with high accuracy compared with the other techniques. Because there is a similarity between the inter-turn frequency component and other machine faults frequency components (mixed air gap eccentricity, unbalance supply voltage) resulting a wrong discussion about the machine condition.
The main objective of the present work is to describe the sensorless control of interior permanent magnet synchronous motor (IPMSM) for embeded systems in traction applications using the Model Reference Adaptive System (MRAS) method for speed estimation. The algorithm of this method has been adapted with the mathematical model of the motorized wheels electric vehicle. The command used is the DTC. Sensorless DTC of IPMS in-wheel motor based on MRAS for electric vehicle is simulated by Matlab/Simulink. The simulation results show the effectiveness of this proposed sensorless DTC control used for embedded system applications.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
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The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
DevOps and Testing slides at DASA ConnectKari Kakkonen
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SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
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Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
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Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
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However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
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The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
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In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
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https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
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This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
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- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
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- How to remove silos in DevSecOps
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- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
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2. 76 Computer Science & Information Technology (CS & IT)
provide fast transient response [1]. Accurate position control is not possible with scalar control
since this requires instantaneous control of the torque. This requires either, instantaneous change
to the stator currents, which is not possible due to energy storage effects, or instantaneous change
to the rotor current which in the case of scalar control is controlled indirectly via the stator
currents. Similarly, whilst scalar control may provide acceptable steady state speed control,
precise and responsive speed control due to load changes requires accurate and responsive torque
control. The vector approach overcomes the sluggish transient response when using scalar control
of AC motors [7].
2. VECTOR CONTROL
Vector control of an Induction motor is also called Field orientation control. In a typical AC
induction motor, three alternating currents electrically displaced by 120◦ are applied to three
stationary stator coils of the motor. The resulting flux from the stator induces alternating currents
in the ‘squirrel cage’ conductors of the rotor to create its own field these fields interact to create
torque. Unlike a DC machine the rotor currents in an AC induction motor cannot be controlled
directly from an external source, but are derived from the interaction between the stator field and
the resultant currents induced in the rotor conductors [13].
Figure 1. Vector control of Induction motor
Vector control of an AC induction motor is analogous to the control of a separately excited DC
motor [7]. In a DC motor the field flux ψf produced by the field current If is perpendicular to the
armature flux ψa produced by the armature current Ia. These fields are decoupled and stationary
with respect to each other. Therefore when the armature current is controlled to control torque the
field flux remains unaffected enabling a fast transient response.
In a vector-controlled drive, the machine stator current vector Is has two components: ids or flux
component and iqs or torque component, as shown in the phasor diagram. These current
components are to be controlled independently, as in a dc machine, to control the flux and torque,
respectively. The ids is oriented in the direction of ψr, and iqs is oriented orthogonally to it. The
controller should make the two inverse transformations, where the unit vector cosθe and sinθe in
the controller should ensure correct alignment of ids in the direction of ψr and iqs at 90◦ ahead of it.
Obviously, the unit vector is the key element for vector control [8]. There are two methods of
vector control based on the derivation of the unit vector. These are the direct (or feedback)
method and indirect (or feed forward) method. For closed-loop flux control in constant-torque
and field weakening regions, ids can be controlled within the programmed flux control loop so that
the inverter always operates in PWM mode [1].
3. Computer Science & Information Technology (CS & IT) 77
3. DRIVE SYSTEM
It has been established that iq and id of the rotating reference frame must be controlled to provide
good dynamic control of the induction motor. Using closed loop control ordered quantities of iq
and id are compared with the actual values measured from the motor. In order to obtain the motor
values, transformations on the measured 3 phase stator currents into the direct and quadrature
components of the rotating reference frame are performed. The resulting error terms are then
transformed back to 3 phase quantities and applied to the motor.
Figure 2. Block diagram of Vector control of Induction motor
The power circuit (Fig.2) consists of a DC source (battery or rectifier DC), PWM IGBT inverter
and cage type induction motor. The signal processing blocks include machine phase current
sensors, signals computation and controller, and the PWM algorithm [3]. The command torque
(Te*) and stator flux (ψs*) generate the active (iqs*) and reactive (ids*) current commands within the
block which are then translated to generate input for PWM controller. The machine terminal
voltages and currents are sensed and converted into stationery frame ds – qs signals. These
signals are then converted to rotating frame. The synchronous control loops then generate Vqs*
and Vds* signals. Vqs* and Vds* signals are then translated using inverse Clarke transformation and
fed as input to PWM controller. The PWM controller receives signals at the input and translates
to gate drive signals for the IGBT inverter [8].
4. RADIAL BASIS FUNCTION NEURAL NETWORK
RBF is a Multilayer Perceptron Network (MLP) which is based on unit computing of non-linear
function of scalar product of input & output. For an auto associative net the training input and
target output vectors are identical. A stored vector can be retrieved from distorted or partial input
if the input is sufficiently similar to it. Auto-associative neural network is basically a feed
forward, fully-connected, multilayer perceptron (MLP) type neural network. The general RBF
network consists of 3 layers, Input layer, Hidden layer, Output layer.
4. 78 Computer Science & Information Technology (CS & IT)
Figure 3. Architecture of RBFNN
No. of neurons in input layer = 3
No. of neurons in hidden layer = 4 (obtained by using k-means algorithm).
No. of neurons in output layer = 3
The input layer is made up of source nodes that connect the network to its environment. The
second layer, the only hidden layer in the network applies a non liner transformation from the
input space to the hidden space. The output layer is linear, supplying the response of the network
to the signal applied to the input layer.
4.1. Algorithm
1. First the input is given to the input layer.
2. The network is simulated and initialized. For deciding the number of neurons in hidden
layer k-means algorithm is used.
3. Iterate until the network converges.
4. Calculate the error between the network’s o/p & the target o/p. if the error isn't in the
desired limit go to step 3 else go to step 5.
5. Observe the performance of the network with the training and the test data. Re-train if
necessary.
4.1. K - means Algorithm
1. Choose initial centres c1,...,ck.
2. While the clusters are changing, repeat step 3 to 4.
3. Assign data point pi to the cluster whose centre C is closest. This can be done by using
Euclidean distance.
4. Update the cluster centres given by :-
C= (1/n)∑ P.
n = number of points in C
5. Computer Science & Information Technology (CS & IT) 79
Figure 4. Flowchart of RBF neural network
5. SIMULATION STUDY
To implement a RBF neural network for drift compensation of stator current, multiplicative errors
were implicated in the stator part of the induction motor. Stator currents were observed for
different values of errors implemented in ia, ib, ic, iaib, ibic & icia ranging from 0.1 to 1 and at
voltages ranging from 210 to 510 to obtain the training data for neural network. The
corresponding stator currents are shown in Figure 5 and 6. By introducing different errors in
Matlab Simulink, 960 sets of training data were obtained. Using this data the RBF neural network
with the implementation of k-means algorithm was trained and tested.
6. 80 Computer Science & Information Technology (CS & IT)
Figure. 5. Stator currents (ia,ib,ic)
Figure.6. Stator currents with error factor 0.1 in ia
6. RESULTS
Vector control of Induction motor was simulated using Matlab Simulink and three stator currents
ia,ib,ic were noted. Multiplicative errors were implicated in the stator currents to obtain the training
data for neural network. The RBF Neural network with the implementation of k-means algorithm
was trained and tested. Every time numbers of clusters and radius in the k-means algorithm were
varied and the result of the k-means algorithm which gives the clusters center and the number of
training data in each cluster were implemented in the RBFNN. Maximum absolute error,
minimum absolute error (target- output) and root mean square error (RMSE) at different radius
and cluster in the network were found to reduce. Figure 7 shows that the minimum RMSE is at
125 clusters. So for 960 sets of training data maximum absolute error was 2.006, minimum
absolute error was 0.00022339 and the RMSE was 0.34525 at 125 clusters and radius 5. The
satisfactory output was obtained for the layer with neurons 3 – 125 – 3 (Input–Hidden–Output).
RBF neural network with implementation of k-means algorithm was trained with 960 sets of data
and satisfactory output was obtained.
7. Computer Science & Information Technology (CS & IT) 81
Figure. 7. Root Mean Square Error (RMSE) Vs cluster.
Table 1 Tested data with trained RBF Neural Network
Input Stator Current Target Stator Current Output Stator Current
Ia Ib Ic Ia Ib Ic Ia Ib Ic
1.5 15 15 15 15 15 15.002 15.002 15.002
15 13 15 15 15 15 14.994 14.994 14.994
15 15 4.5 15 15 15 15.007 15.007 15.007
6 17 17 17 17 17 17.007 17.007 17.007
17 3.5 17 17 17 17 16.993 16.993 16.993
17 17 8 17 17 17 16.998 16.998 16.998
8. 82 Computer Science & Information Technology (CS & IT)
RBFNN was tested and the output shown in Table1 was obtained. It can be observed that the drift
in stator current due to various faults in all the three phases are compensated by the neural
network validating that trained neural network restores back the closest possible original value of
stator current achieving the compensation in the stator current of the Induction motor.
7. CONCLUSION
Vector control of Induction motor using Radial basis function neural network has been
implemented in this paper. The neural network was trained with 960 sets of input data and tested
to obtain a satisfactory output. The result of the K-MEANS algorithm was implemented in the
RBFNN and hence the stator currents were restored to its original values. In this paper,
supervised learning algorithm has been adopted to train the neural network. Artificial neural
network can be implemented by either using supervised network or fixed weight network or both
the types of network. By implementing the above said networks, performance of Induction motor
can be improved as any change in the stator current has been compensated by the trained neural
network and henceforth its performance.
REFERENCES
[1] A.K.Sharma,R.A.Gupta, Laxmi Srivastava.: Performance of ANN based indirect vector control
induction motor drive, Journal of theoritical and applied Information technology. IEEE trans 2007.
[2] M.H. Jokar, B. Abdi, M. Ardebili.: Vector Control of Induction Motors Using Radial Basis Function
Neural Network. (2007 IEEE trans.)
[3] L.Galotto, J.O.P. Pinto, B. Ozpineci, L.C.Leite, L.E. Borges da silva,: Sensor compensation in motor
drives using Kernel Regressio., IEEE International Electric Machines and drives conference,2007
[4] L. Galotto, Bimal. K. Bose, L.C. Leite, J.O.P. Pinto, L.E. Borges da silva, Germano Lambert-Torres.:
Auto-Associative Neural Network based sensor drift compensation in Indirect controlled drive
system. IEEE Industrial Electronics society,2007.
[5] Kamel Baddari, Tahar Aifa, Noureddine Djarfour, Jalal Ferahtia.:Application of Radial Basis
Function Artificial Neural Network to seismic data inversion. Science Direct Computers &
Geoscience 35,2009(2338-2344).
[6] A. El-Antably, L. Xiaogang and R. Martin.:System simulation of fault conditions in the components
of the electric drive system. IEEE journal 1993.
[7] N. Reitere, D. Roye and P. Mannevy.:Vector based investigation of induction motor drive under fault
operations. IEEE 1997
[8] Kramer. M .A.:Auto-associative Neural Networks. AIChE Journal, Vol.16
[9] X.Xu, R.N.De Donker and D.W.Novotny.: A stator flux oriented induction machine drive. IEEE 1998
[10] J.O.P.Pinto, B.K.Bose, L.E.Borges.: A stator flux oriented vector controlled induction motor drive
with space-vector PWM and flux vector synthesis by neural networks. IEEE trans. on Industry
Applications,Vol.37,No.5, 2001
[11] J.O.P.Pinto, B.K.Bose, L.E.Borges, and M.P.Kazmierkowski.: A neural network based space vector
PWM controller for voltage fed induction motor drive.IEEE trans. 2000.
[12] B.K.Bose,Ed.,Power Electronics and variable frequency drives, IEEE Press, New York, 1996.
[13] B.K.Bose., Modern Power Electronics and AC Drives, Prentice Hall, Upper Saddle River, NJ,2002
9. Computer Science & Information Technology (CS & IT) 83
AUTHORS
Uthra.R completed her graduation in Electrical & Electronics from Madras University
in 2002 and Masters in Power Electronics & Drives from SRM University in 2010. Her
area of interest is artificial intelligence in power Electronics & Drives. She is currently
working as Assistant Professor in SRM University.
N.Kalaiarasi received the Bachelor of Engineering in Electronics and Communication
Engineering from Periyar University in the year 2002 and Master of Engineering in
Power Electronics and Drives from college of Engineering, Anna University in the
year 2004. She is currently doing Research in the area of solar energy. She is currently
working as Assistant professor (Sr.G) in the Department of Electrical and Electronics
Engineering, SRM University, Chennai, India. Her area of interest includes Power
Electronics, Digital Signal Processing, and Fuzzy Logic applications in Drives, solar
energy.
Srinivas Arun Tej P received the Bachelor of Engineering in Electrical and Electronics Engineering from
Jawaharlal Nehru Technological University in the year 2011 and Master of Engineering in Power
Electronics and Drives from SRM University in the year 2013.