This document presents research on sensorless speed control of an induction motor using predictive current and torque controllers. It begins with an abstract summarizing the research, which involves using a closed-loop observer system and predictive controllers to control an induction motor drive without requiring direct measurement of motor speed or flux. The document then provides background information on sensorless induction motor control and challenges associated with it. It describes the proposed control system, which uses a closed-loop observer to estimate motor flux and speed, along with a predictive current controller and predictive torque controller. Simulation results are presented confirming the effectiveness of the proposed sensorless control approach.
The speed estimation technique of induction machines has become a non-trivial task. For estimating the speed of an induction motor precisely and accurately an optimum state estimator is necessary. This paper deals with the performance analysis of induction motor drives using a recursive, optimum state estimator. This technique uses a full order state space Extended Kalman Filter (EKF) model where the rotor flux, rotor speed and stator currents are estimated. A major challenge with induction motor occurs at very low and at near zero speed. In such cases, information about the rotor parameters with respect to stator side become unobservable while using the synchronously rotating reference frame. To overcome this lost coupling effect, EKF observer linearizes the non-linear parameter in every sampling period and estimates the states and machine parameters simultaneously. The proposed algorithm is tuned to obtain least error in estimated speed. Any error found is further optimized using a non-linear fuzzy controller to obtain improved performance of the drive.
Low Speed Estimation in Sensorless Direct Torque Controlled Induction Motor D...IJPEDS-IAES
Sensorless Direct Torque Control (DTC) is a powerful control scheme for
high performance control of induction motor (IM) drives, which provides
very quick dynamic response with simple structure and a decoupled control
of torque and flux. The performance of the DTC drive greatly depends on the
accuracy of the estimated flux components, torque and speed, using
monitored stator voltages and currents. Low speed estimation is a great
challenge because of the presence of transient offset, drift and domination of
ohmic voltage drop.Extended Kalman filter (EKF) is a non linear adaptive
filter which performs the process of finding the best estimate from the noisy
data based on state space technique and recursive algorithm.This paper
mainly focuses on the accurate estimation of speed ranging from very low
speed to rated speed using the equation of motion. A new state space model
of the IM is developed for estimation in EKF, with load torque as an input
variable and not as an estimated quantity which is the case in most previous
studies.The developed algorithm is validated using MATLAB-Simulink
platform for speeds ranging from low speed to rated speed at rated torque and
at various torque conditions. An exhaustive analysis is carried out to validate
the performance of DTC Induction motor drive especially at the low speeds.
The results are promising for accurate estimation of speed ranging from low
speed to rated speed using EKF.
Nowadays, the elimination of the speed sensor in Permanent Magnet Synchronous Machine (PMSM) is greatly recommended to increase efficiency and reduce the cost of the drives. This paper proposes a simple estimator for speed and rotor position of PMSM drives using adaptive controller. The novelties of the proposed method are the simple estimator equations and the absence of the voltage probe which depend on direct and quadrature reference current only. The simplified mathematical model of the PMSM is formulated by using V-I model, based on adaptive control. Then, the speed estimation error of the voltage and current model based are analyzed. Thus, an adaptation mechanism model is established to cancel the error of the measured and estimated d-q currents. Since the output of the estimator is the position feedback, the performances of speed responses are presented. The hardware implementation of proposed sensorless drives is realized via dSPACE DS11103 panel. dSPACE Real Time Implementation (RTI) is the linkage between software and hardware set-up. It automatically processes the MATLAB Simulink model into dSPACE DS11103 processor. The experimental-hardware results demonstrate that the speed and position estimator of the proposed method is able to control the PMSM drives for forward and reverse of speed command, acceleration, deceleration and robustness to load disturbance.
Comparison Analysis of Indirect FOC Induction Motor Drive using PI, Anti-Wind...IAES-IJPEDS
This paper presents the speed performance analysis of indirect Field Oriented Control (FOC) induction motor drive by applying Proportional Integral (PI) controller, PI with Anti-Windup (PIAW) and Pre- Filter (PF). The objective of this experiment is to have quantitative comparison between the controller strategies towards the performance of the motor in term of speed tracking and load rejection capability in low, medium and rated speed operation. In the first part, PI controller is applied to the FOC induction motor drive which the gain is obtained based on determined Induction Motor (IM) motor parameters. Secondly an AWPI strategy is added to the outer loop and finally, PF is added to the system. The Space Vector Pulse Width Modulation (SVPWM) technique is used to control the voltage source inverter and complete vector control scheme of the IM drive is tested by using a DSpace 1103 controller board. The analysis of the results shows that, the PI and AWPI controller schemes produce similar performance at low speed operation. However, for the medium and rated speed operation the AWPI scheme shown significant improvement in reducing the overshoot problem and improving the setting time. The PF scheme on the other hand, produces a slower speed and torque response for all tested speed operation. All schemes show similar performance for load disturbance rejection capability.
The paper proposes Direct Torque Control (DTC) of a five-phase induction motor drive with reduced torque ripple. The method presented here is the DTC Backstepping based on the classic DTC working with a constant switching frequency of the inverter. Another remarkable aspect is the complexity of the method proposed, both in the control unit of the inverter and in the number of correctors necessary for the control of the torque. The selection table and hysteresis have been eliminated. This method significantly improves the torque and flux oscillations and improves the dynamics of the drive by making it less sensitive to load torque disturbances. The proposed method is developed and designed using Matlab/SIMULINK to show the eectiveness and performances of the DTC-Backstepping.
For Induction motor is a system that works at their speed, nevertheless there are applications at which the speed operations are needed. The control of range of speed of induction motor techniques is available. The robust control is used with induction motor and the performance of the system with the controller will be improved. The mathematical model to the controller, which were coded in MATLAB. The modeling and controller will be shown by the conditions of robustness of be less than one.
Speed and Torque Control of Mechanically Coupled Permanent Magnet Direct Curr...IDES Editor
A new controller is designed for speed and torque
control of a Permanent Magnet DC motor based on
measurements of speed and current. This research work
focuses on investigating the effects of control of the speed and
torque of two brushless dc motors that are mechanically
coupled. Two controller design methods: the Root Locus
method and Bode Plot method as well as two controllers:
Proportional-Integral-Derivative (PID) and Proportional-
Integral (PI) are used to obtain the control objectives of speed
control and torque control. The simulation is performed using
MATLAB/SIMULINK software. The effects of varying the
controller gains on the system performance is studied and
quantified. The simulation results show that the speed control
objectives of the motor are satisfied even in the case of torque
disturbance from the other motor.
The speed estimation technique of induction machines has become a non-trivial task. For estimating the speed of an induction motor precisely and accurately an optimum state estimator is necessary. This paper deals with the performance analysis of induction motor drives using a recursive, optimum state estimator. This technique uses a full order state space Extended Kalman Filter (EKF) model where the rotor flux, rotor speed and stator currents are estimated. A major challenge with induction motor occurs at very low and at near zero speed. In such cases, information about the rotor parameters with respect to stator side become unobservable while using the synchronously rotating reference frame. To overcome this lost coupling effect, EKF observer linearizes the non-linear parameter in every sampling period and estimates the states and machine parameters simultaneously. The proposed algorithm is tuned to obtain least error in estimated speed. Any error found is further optimized using a non-linear fuzzy controller to obtain improved performance of the drive.
Low Speed Estimation in Sensorless Direct Torque Controlled Induction Motor D...IJPEDS-IAES
Sensorless Direct Torque Control (DTC) is a powerful control scheme for
high performance control of induction motor (IM) drives, which provides
very quick dynamic response with simple structure and a decoupled control
of torque and flux. The performance of the DTC drive greatly depends on the
accuracy of the estimated flux components, torque and speed, using
monitored stator voltages and currents. Low speed estimation is a great
challenge because of the presence of transient offset, drift and domination of
ohmic voltage drop.Extended Kalman filter (EKF) is a non linear adaptive
filter which performs the process of finding the best estimate from the noisy
data based on state space technique and recursive algorithm.This paper
mainly focuses on the accurate estimation of speed ranging from very low
speed to rated speed using the equation of motion. A new state space model
of the IM is developed for estimation in EKF, with load torque as an input
variable and not as an estimated quantity which is the case in most previous
studies.The developed algorithm is validated using MATLAB-Simulink
platform for speeds ranging from low speed to rated speed at rated torque and
at various torque conditions. An exhaustive analysis is carried out to validate
the performance of DTC Induction motor drive especially at the low speeds.
The results are promising for accurate estimation of speed ranging from low
speed to rated speed using EKF.
Nowadays, the elimination of the speed sensor in Permanent Magnet Synchronous Machine (PMSM) is greatly recommended to increase efficiency and reduce the cost of the drives. This paper proposes a simple estimator for speed and rotor position of PMSM drives using adaptive controller. The novelties of the proposed method are the simple estimator equations and the absence of the voltage probe which depend on direct and quadrature reference current only. The simplified mathematical model of the PMSM is formulated by using V-I model, based on adaptive control. Then, the speed estimation error of the voltage and current model based are analyzed. Thus, an adaptation mechanism model is established to cancel the error of the measured and estimated d-q currents. Since the output of the estimator is the position feedback, the performances of speed responses are presented. The hardware implementation of proposed sensorless drives is realized via dSPACE DS11103 panel. dSPACE Real Time Implementation (RTI) is the linkage between software and hardware set-up. It automatically processes the MATLAB Simulink model into dSPACE DS11103 processor. The experimental-hardware results demonstrate that the speed and position estimator of the proposed method is able to control the PMSM drives for forward and reverse of speed command, acceleration, deceleration and robustness to load disturbance.
Comparison Analysis of Indirect FOC Induction Motor Drive using PI, Anti-Wind...IAES-IJPEDS
This paper presents the speed performance analysis of indirect Field Oriented Control (FOC) induction motor drive by applying Proportional Integral (PI) controller, PI with Anti-Windup (PIAW) and Pre- Filter (PF). The objective of this experiment is to have quantitative comparison between the controller strategies towards the performance of the motor in term of speed tracking and load rejection capability in low, medium and rated speed operation. In the first part, PI controller is applied to the FOC induction motor drive which the gain is obtained based on determined Induction Motor (IM) motor parameters. Secondly an AWPI strategy is added to the outer loop and finally, PF is added to the system. The Space Vector Pulse Width Modulation (SVPWM) technique is used to control the voltage source inverter and complete vector control scheme of the IM drive is tested by using a DSpace 1103 controller board. The analysis of the results shows that, the PI and AWPI controller schemes produce similar performance at low speed operation. However, for the medium and rated speed operation the AWPI scheme shown significant improvement in reducing the overshoot problem and improving the setting time. The PF scheme on the other hand, produces a slower speed and torque response for all tested speed operation. All schemes show similar performance for load disturbance rejection capability.
The paper proposes Direct Torque Control (DTC) of a five-phase induction motor drive with reduced torque ripple. The method presented here is the DTC Backstepping based on the classic DTC working with a constant switching frequency of the inverter. Another remarkable aspect is the complexity of the method proposed, both in the control unit of the inverter and in the number of correctors necessary for the control of the torque. The selection table and hysteresis have been eliminated. This method significantly improves the torque and flux oscillations and improves the dynamics of the drive by making it less sensitive to load torque disturbances. The proposed method is developed and designed using Matlab/SIMULINK to show the eectiveness and performances of the DTC-Backstepping.
For Induction motor is a system that works at their speed, nevertheless there are applications at which the speed operations are needed. The control of range of speed of induction motor techniques is available. The robust control is used with induction motor and the performance of the system with the controller will be improved. The mathematical model to the controller, which were coded in MATLAB. The modeling and controller will be shown by the conditions of robustness of be less than one.
Speed and Torque Control of Mechanically Coupled Permanent Magnet Direct Curr...IDES Editor
A new controller is designed for speed and torque
control of a Permanent Magnet DC motor based on
measurements of speed and current. This research work
focuses on investigating the effects of control of the speed and
torque of two brushless dc motors that are mechanically
coupled. Two controller design methods: the Root Locus
method and Bode Plot method as well as two controllers:
Proportional-Integral-Derivative (PID) and Proportional-
Integral (PI) are used to obtain the control objectives of speed
control and torque control. The simulation is performed using
MATLAB/SIMULINK software. The effects of varying the
controller gains on the system performance is studied and
quantified. The simulation results show that the speed control
objectives of the motor are satisfied even in the case of torque
disturbance from the other motor.
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.
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.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
High frequency signal injection method for sensorless permanent magnet synchr...TELKOMNIKA JOURNAL
The objective of this project is to design a high frequency signal injection method for sensorless control of permanent magnet synchronous motor (PMSM) drives. Generally, the PMSM drives control requires the appearance of speed and positon sensor to measure the motor speed hence to feedback the information for variable speed drives operation. The usage of the sensor will increase the size, cost, extra hardwire and feedback devices. Therefore, there is motivation to eliminate this type of sensor by injecting high frequency signal and utilizing the electrical parameter from the motor so that the speed and positon of rotor can be estimated. The proposed position and speed sensorless control method using high frequency signal injection together with all the power electronic circuit are modelled using Simulink. PMSM sensorless driveis simulated and the results are analyzed in terms of speed, torque and stator current response without load disturbance but under the specification of varying speed, forward to reverse operation, reverse to forward operation and step change in reference speed. The results show that the signal injection method performs well during start-up and low speed operation.
Speed controller design for three-phase induction motor based on dynamic ad...IJECEIAES
Three-phase induction motor (TIM) is widely used in industrial application like paper mills, water treatment and sewage plants in the urban area. In these applications, the speed of TIM is very important that should be not varying with applied load torque. In this study, direct on line (DOL) motor starting without controller is modelled to evaluate the motor response when connected directly to main supply. Conventional PI controller for stator direct current and stator quadrature current of induction motor are designed as an inner loop controller as well as a second conventional PI controller is designed in the outer loop for controlling the TIM speed. Proposed combined PI-lead (CPIL) controllers for inner and outer loops are designed to improve the overall performance of the TIM as compared with the conventional controller. In this paper, dynamic adjustment grasshopper optimization algorithm (DAGOA) is proposed for tuning the proposed controller of the system. Numerical results based on well-selected test function demonstrate that DAGOA has a better performance in terms of speed of convergence, solution accuracy and reliability than SGOA. The study results revealed that the currents and speed of TIM system using CPIL-DAGOA are faster than system using conventional PI and CPIL controllers tuned by SGOA. Moreover, the speed controller of TIM system with CPIL controlling scheme based on DAGOA reached the steady state faster than others when applied load torque.
Permanent magnet synchronous motors (PMSMs) are increasingly used in high performance variable speed drives of many industrial applications. PMSM has many features, like high efficiency, compactness, high torque to inertia ratio, rapid dynamic response, simple modeling and control, and maintenance free operation. Presence of position sensors presents several disadvantages, such as reduced reliability, susceptibility to noise, additional cost and weight and increased complexity of the drive system. For these reasons, the development of alternative indirect methods for speed and position control becomes an important research topic. Advantages of sensorless control are reduced hardware complexity, low cost, reduced size, cable elimination, increased noise immunity, increased reliability and decreased maintenance. The key problem in sensorless vector control of ac drives is the accurate dynamic estimation of the stator flux vector over a wide speed range using only terminal variables (currents and voltages). The difficulty comprises state estimation at very low speeds where the fundamental excitation is low and the observer performance tends to be poor. Moreover, the noises of system and measurements are considered other main problems. This paper presents a comprehensive study of the different sliding mode observer methods of speed and position estimations for sensorless control of PMSM drives.
Comparison of Estimated Torques Using Low Pass Filter and Extended Kalman Fil...IAES-IJPEDS
Torque calculation process is one of the major concerns for controlling induction motors in industry, which requires very accurate state estimation of unmeasurable variables of nonlinear models. This can be solved if the variables used for torque calculation is accurately estimated. This paper presents a torque calculation based on a voltage model represented with a low-pass filter (LPF), and an extended Kalman filter (EKF). The experimental results showed that the estimated torque at low speed based on EKF is more accurate in the expense of more complicated and larger computational time.
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.
STATOR FLUX OPTIMIZATION ON DIRECT TORQUE CONTROL WITH FUZZY LOGIC cscpconf
The Direct Torque Control (DTC) is well known as an effective control technique for high
performance drives in a wide variety of industrial applications and conventional DTC technique
uses two constant reference value: torque and stator flux. In this paper, fuzzy logic based stator
flux optimization technique for DTC drives that has been proposed. The proposed fuzzy logic
based stator flux optimizer self-regulates the stator flux reference using induction motor load situation without need of any motor parameters. Simulation studies have been carried out with Matlab/Simulink to compare the proposed system behaviors at vary load conditions. Simulation results show that the performance of the proposed DTC technique has been improved and especially at low-load conditions torque ripple are greatly reduced with respect to the conventional DTC
Speed Sensorless Vector Control of Unbalanced Three-Phase Induction Motor wit...IAES-IJPEDS
This paper presents a technique for speed sensorless Rotor Flux Oriented Control (RFOC) of 3-phase Induction Motor (IM) under open-phase fault (unbalanced or faulty IM). The presented RFOC strategy is based on rotational transformation. An adaptive sliding mode control system with an adaptive switching gain is proposed instead of the speed PI controller. Using an adaptive sliding mode control causes the proposed speed sensorless RFOC drive system to become insensitive to uncertainties such as load disturbances and parameter variations. Moreover, with adaptation of the sliding switching gain, calculation of the system uncertainties upper bound is not needed. Finally, simulation results have been presented to confirm the good performance of the proposed method.
Implementation of pi, fuzzy & ann controllers to improve dynamic response...eSAT Journals
Abstract Nowadays, vector controlled induction motor drives with variable speed applications are widely used in order to achieve good dynamic performance and wide speed control. In this paper a new method of controlling technique based on Artificial Neural Network is proposed to improve the speed control of indirect vector controlled induction motor drive. Indirect vector controlled induction motor with conventional PI controller is developed and is replaced with Fuzzy logic controller to overcome the problem of overshoot occurred in conventional PI controller. To obtain quick steady state response and better speed control, ANN technique is proposed and implemented using MATLAB/Simulink. In this paper the speed, torque and stator voltage responses with conventional PI controller, Fuzzy logic controller and proposed artificial neural network based controller are compared and found that the proposed ANN based controller showed increased dynamic performance. Keywords: ANN, FLC, PI controller, IVCIM
A Novel Rotor Resistance Estimation Technique for Vector Controlled Induction...IAES-IJPEDS
Induction motor with indirect field oriented control is well suited for high
performance applications due to its excellent dynamic behavior. However it
is sensitive to variations in rotor time constant, especially variation in rotor
resistance. In this study a scheme based on the Rotor flux Model Reference
Adaptive Controller is used for on line identification of the rotor resistance
and thus improving the steady state performance of the drive. The overriding
feature of this estimation technique is the accurate identification of rotor
resistance during transient and steady state conditions for drive operation at
full load and at zero speed condition. Moroever, the effectiveness of the TS
fuzzy controller utilizing rotor flux for online estimation of rotor resistance
for four quadrant operation of motor drive is investigated and compared with
the conventional PI and Mamdani fuzzy controller.Simulation results in
MATLAB/Simulink environment have been presented to confirm the
effectiviness of the proposed technique.
Backstepping Control for a Five-Phase Permanent Magnet Synchronous Motor DriveIJPEDS-IAES
This paper deals with the synthesis of a speed control strategy for a fivephase
permanent magnet synchronous motor (PMSM) drive based on
backstepping controller. The proposed control strategy considers the
nonlinearities of the system in the control law. The stability of the
backstepping control strategy is proved by the Lyapunov theory. Simulated
results are provided to verify the feasibility of the backstepping control
strategy.
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.
A Novel Technique for Tuning PI-controller in Switched Reluctance Motor Drive...IJECEIAES
This paper presents, an optimal basic speed controller for switched reluctance motor (SRM) based on ant colony optimization (ACO) with the presence of good accuracies and performances. The control mechanism consists of proportional-integral (PI) speed controller in the outer loop and hysteresis current controller in the inner loop for the three phases, 6/4 switched reluctance motor. Because of nonlinear characteristics of a SRM, ACO algorithm is employed to tune coefficients of PI speed controller by minimizing the time domain objective function. Simulations of ACO based control of SRM are carried out using MATLAB /SIMULINK software. The behavior of the proposed ACO has been estimated with the classical Ziegler- Nichols (ZN) method in order to prove the proposed approach is able to improve the parameters of PI chosen by ZN method. Simulations results confirm the better behavior of the optimized PI controller based on ACO compared with optimized PI controller based on classical Ziegler-Nichols method.
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.
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.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
High frequency signal injection method for sensorless permanent magnet synchr...TELKOMNIKA JOURNAL
The objective of this project is to design a high frequency signal injection method for sensorless control of permanent magnet synchronous motor (PMSM) drives. Generally, the PMSM drives control requires the appearance of speed and positon sensor to measure the motor speed hence to feedback the information for variable speed drives operation. The usage of the sensor will increase the size, cost, extra hardwire and feedback devices. Therefore, there is motivation to eliminate this type of sensor by injecting high frequency signal and utilizing the electrical parameter from the motor so that the speed and positon of rotor can be estimated. The proposed position and speed sensorless control method using high frequency signal injection together with all the power electronic circuit are modelled using Simulink. PMSM sensorless driveis simulated and the results are analyzed in terms of speed, torque and stator current response without load disturbance but under the specification of varying speed, forward to reverse operation, reverse to forward operation and step change in reference speed. The results show that the signal injection method performs well during start-up and low speed operation.
Speed controller design for three-phase induction motor based on dynamic ad...IJECEIAES
Three-phase induction motor (TIM) is widely used in industrial application like paper mills, water treatment and sewage plants in the urban area. In these applications, the speed of TIM is very important that should be not varying with applied load torque. In this study, direct on line (DOL) motor starting without controller is modelled to evaluate the motor response when connected directly to main supply. Conventional PI controller for stator direct current and stator quadrature current of induction motor are designed as an inner loop controller as well as a second conventional PI controller is designed in the outer loop for controlling the TIM speed. Proposed combined PI-lead (CPIL) controllers for inner and outer loops are designed to improve the overall performance of the TIM as compared with the conventional controller. In this paper, dynamic adjustment grasshopper optimization algorithm (DAGOA) is proposed for tuning the proposed controller of the system. Numerical results based on well-selected test function demonstrate that DAGOA has a better performance in terms of speed of convergence, solution accuracy and reliability than SGOA. The study results revealed that the currents and speed of TIM system using CPIL-DAGOA are faster than system using conventional PI and CPIL controllers tuned by SGOA. Moreover, the speed controller of TIM system with CPIL controlling scheme based on DAGOA reached the steady state faster than others when applied load torque.
Permanent magnet synchronous motors (PMSMs) are increasingly used in high performance variable speed drives of many industrial applications. PMSM has many features, like high efficiency, compactness, high torque to inertia ratio, rapid dynamic response, simple modeling and control, and maintenance free operation. Presence of position sensors presents several disadvantages, such as reduced reliability, susceptibility to noise, additional cost and weight and increased complexity of the drive system. For these reasons, the development of alternative indirect methods for speed and position control becomes an important research topic. Advantages of sensorless control are reduced hardware complexity, low cost, reduced size, cable elimination, increased noise immunity, increased reliability and decreased maintenance. The key problem in sensorless vector control of ac drives is the accurate dynamic estimation of the stator flux vector over a wide speed range using only terminal variables (currents and voltages). The difficulty comprises state estimation at very low speeds where the fundamental excitation is low and the observer performance tends to be poor. Moreover, the noises of system and measurements are considered other main problems. This paper presents a comprehensive study of the different sliding mode observer methods of speed and position estimations for sensorless control of PMSM drives.
Comparison of Estimated Torques Using Low Pass Filter and Extended Kalman Fil...IAES-IJPEDS
Torque calculation process is one of the major concerns for controlling induction motors in industry, which requires very accurate state estimation of unmeasurable variables of nonlinear models. This can be solved if the variables used for torque calculation is accurately estimated. This paper presents a torque calculation based on a voltage model represented with a low-pass filter (LPF), and an extended Kalman filter (EKF). The experimental results showed that the estimated torque at low speed based on EKF is more accurate in the expense of more complicated and larger computational time.
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.
STATOR FLUX OPTIMIZATION ON DIRECT TORQUE CONTROL WITH FUZZY LOGIC cscpconf
The Direct Torque Control (DTC) is well known as an effective control technique for high
performance drives in a wide variety of industrial applications and conventional DTC technique
uses two constant reference value: torque and stator flux. In this paper, fuzzy logic based stator
flux optimization technique for DTC drives that has been proposed. The proposed fuzzy logic
based stator flux optimizer self-regulates the stator flux reference using induction motor load situation without need of any motor parameters. Simulation studies have been carried out with Matlab/Simulink to compare the proposed system behaviors at vary load conditions. Simulation results show that the performance of the proposed DTC technique has been improved and especially at low-load conditions torque ripple are greatly reduced with respect to the conventional DTC
Speed Sensorless Vector Control of Unbalanced Three-Phase Induction Motor wit...IAES-IJPEDS
This paper presents a technique for speed sensorless Rotor Flux Oriented Control (RFOC) of 3-phase Induction Motor (IM) under open-phase fault (unbalanced or faulty IM). The presented RFOC strategy is based on rotational transformation. An adaptive sliding mode control system with an adaptive switching gain is proposed instead of the speed PI controller. Using an adaptive sliding mode control causes the proposed speed sensorless RFOC drive system to become insensitive to uncertainties such as load disturbances and parameter variations. Moreover, with adaptation of the sliding switching gain, calculation of the system uncertainties upper bound is not needed. Finally, simulation results have been presented to confirm the good performance of the proposed method.
Implementation of pi, fuzzy & ann controllers to improve dynamic response...eSAT Journals
Abstract Nowadays, vector controlled induction motor drives with variable speed applications are widely used in order to achieve good dynamic performance and wide speed control. In this paper a new method of controlling technique based on Artificial Neural Network is proposed to improve the speed control of indirect vector controlled induction motor drive. Indirect vector controlled induction motor with conventional PI controller is developed and is replaced with Fuzzy logic controller to overcome the problem of overshoot occurred in conventional PI controller. To obtain quick steady state response and better speed control, ANN technique is proposed and implemented using MATLAB/Simulink. In this paper the speed, torque and stator voltage responses with conventional PI controller, Fuzzy logic controller and proposed artificial neural network based controller are compared and found that the proposed ANN based controller showed increased dynamic performance. Keywords: ANN, FLC, PI controller, IVCIM
A Novel Rotor Resistance Estimation Technique for Vector Controlled Induction...IAES-IJPEDS
Induction motor with indirect field oriented control is well suited for high
performance applications due to its excellent dynamic behavior. However it
is sensitive to variations in rotor time constant, especially variation in rotor
resistance. In this study a scheme based on the Rotor flux Model Reference
Adaptive Controller is used for on line identification of the rotor resistance
and thus improving the steady state performance of the drive. The overriding
feature of this estimation technique is the accurate identification of rotor
resistance during transient and steady state conditions for drive operation at
full load and at zero speed condition. Moroever, the effectiveness of the TS
fuzzy controller utilizing rotor flux for online estimation of rotor resistance
for four quadrant operation of motor drive is investigated and compared with
the conventional PI and Mamdani fuzzy controller.Simulation results in
MATLAB/Simulink environment have been presented to confirm the
effectiviness of the proposed technique.
Backstepping Control for a Five-Phase Permanent Magnet Synchronous Motor DriveIJPEDS-IAES
This paper deals with the synthesis of a speed control strategy for a fivephase
permanent magnet synchronous motor (PMSM) drive based on
backstepping controller. The proposed control strategy considers the
nonlinearities of the system in the control law. The stability of the
backstepping control strategy is proved by the Lyapunov theory. Simulated
results are provided to verify the feasibility of the backstepping control
strategy.
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.
A Novel Technique for Tuning PI-controller in Switched Reluctance Motor Drive...IJECEIAES
This paper presents, an optimal basic speed controller for switched reluctance motor (SRM) based on ant colony optimization (ACO) with the presence of good accuracies and performances. The control mechanism consists of proportional-integral (PI) speed controller in the outer loop and hysteresis current controller in the inner loop for the three phases, 6/4 switched reluctance motor. Because of nonlinear characteristics of a SRM, ACO algorithm is employed to tune coefficients of PI speed controller by minimizing the time domain objective function. Simulations of ACO based control of SRM are carried out using MATLAB /SIMULINK software. The behavior of the proposed ACO has been estimated with the classical Ziegler- Nichols (ZN) method in order to prove the proposed approach is able to improve the parameters of PI chosen by ZN method. Simulations results confirm the better behavior of the optimized PI controller based on ACO compared with optimized PI controller based on classical Ziegler-Nichols method.
http://inarocket.com
Learn BEM fundamentals as fast as possible. What is BEM (Block, element, modifier), BEM syntax, how it works with a real example, etc.
Content personalisation is becoming more prevalent. A site, it's content and/or it's products, change dynamically according to the specific needs of the user. SEO needs to ensure we do not fall behind of this trend.
Lightning Talk #9: How UX and Data Storytelling Can Shape Policy by Mika Aldabaux singapore
How can we take UX and Data Storytelling out of the tech context and use them to change the way government behaves?
Showcasing the truth is the highest goal of data storytelling. Because the design of a chart can affect the interpretation of data in a major way, one must wield visual tools with care and deliberation. Using quantitative facts to evoke an emotional response is best achieved with the combination of UX and data storytelling.
Succession “Losers”: What Happens to Executives Passed Over for the CEO Job?
By David F. Larcker, Stephen A. Miles, and Brian Tayan
Stanford Closer Look Series
Overview:
Shareholders pay considerable attention to the choice of executive selected as the new CEO whenever a change in leadership takes place. However, without an inside look at the leading candidates to assume the CEO role, it is difficult for shareholders to tell whether the board has made the correct choice. In this Closer Look, we examine CEO succession events among the largest 100 companies over a ten-year period to determine what happens to the executives who were not selected (i.e., the “succession losers”) and how they perform relative to those who were selected (the “succession winners”).
We ask:
• Are the executives selected for the CEO role really better than those passed over?
• What are the implications for understanding the labor market for executive talent?
• Are differences in performance due to operating conditions or quality of available talent?
• Are boards better at identifying CEO talent than other research generally suggests?
It is known that controlling the speed of a three phase Induction Motor (IM) under different operating conditions is an important task and this can be accomplished through the process of controlling the applied voltage on its stator circuit. Conventional Proportional- Integral- Differeantional (PID) controller takes long time in selecting the error signal gain values. In this paper a hybrid Fuzzy Logic Controller (FLC) with Genetic Algorithm (GA) is proposed to reduce the selected time for the optimized error signal gain values and as a result inhances the controller and system performance. The proposed controller FL with GA is designed, modeled and simulated using MATLAB/ software under different load torque motor operating condition. The simulation result shows that the closed loop system performance efficiency under the controller has a maximum value of 95.92%. In terms of efficiency and at reference speed signal of 146.53 rad/sec, this system performance shows an inhancement of 0.67%,0.49% and 0.05% with respect to the closed loop system efficiency performance of the PID, FL, and PID with GA controllers respectively. Also the simulation result of the well designed and efficient GA in speeding up the process of selecting the gain values, makes the system to have an efficiency improvement of 14.42% with respect to the open loop system performance.
Convergence Parameter Analysis for Different Metaheuristic Methods Control Co...IJPEDS-IAES
This paper is an extension of our previous work, which discussed the
difficulty in implementing different methods of resistance emulation
techniques on the hardware due to its control constant estimation delay. In
order to get rid of the delay this paper attempts to include the meta-heuristic
methods for the control constants of the controller. To achieve the minimum
Total Harmonic Disturbance (THD) in the AC side of the converter modern
meta-heuristic methods are compared with the traditional methods. The
convergence parameters, which are primary for the earlier estimation of the
control constants, are compared with the measured parameters, tabulated and
tradeoff inference is done among the methods. This kind of implementation
does not need the mathematical model of the system under study for finding
the control constants. The parameters considered for estimation are
population size, maximum number of epochs, and global best solution of the
control constants, best THD value and execution time. MatlabTM /Simulink
based simulation is optimized with the M-file based optimization techniques
like Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Cuckoo
Search Algorithm, Gravity Search Algorithm, Harmony Search Algorithm
and Bat Algorithm.
Modeling and analysis of field-oriented control based permanent magnet synch...IJECEIAES
The permanent magnet synchronous motor (PMSM) acts as an electrical motor mainly used in many diverse applications. The controlling of the PMSM drive is necessary due to frequent usage in various systems. The conventional proportional-integral-derivative (PID) controller’s drawbacks are overcome with fuzzy logic controller (FLC) and adopted in the PMSM drive system. In this manuscript, an efficient field-oriented control (FOC) based PMSM drive system using a fuzzy logic controller (FLC) is modeled to improve the speed and torque response of the PMSM. The PMSM drive system is modeled using abc to αβ and αβ to abc transformation, 2-level space vector pulse width modulation (SVPWM), AC to DC rectifier with an inverter, followed by PMSM drive, proportional integral (PI) controller along with FLC. The FLC’s improved fuzzy rule set is adopted to provide faster speed response, less % overshoot time, and minimal steady-state error of the PMSM drive system. The simulation results of speed response, torque response, speed error, and phase currents are analyzed. The FLC-based PMSM drive is compared with the conventional PID-based PMSM drive system with better improvements in performance metrics.
This research proposes the control system structure for a small-scale wind turbine. Significantly, the maximum power point tracking algorithm (MPPT) and the pitch angle controller are deeply analyzed; this is the base for proposing the strategy of the MPPT algorithm combined with pitch-angle control in a wide speed range of wind. This article also researches the converters, then analyses the advantages of each converter to choose the suitable converter for the small-scale wind turbine. In the MPPT algorithm design, the expert experience takes advantage through the fuzzy controller. The pitch angle controller is built based on the PID controller with its parameters adjusted by Fuzzy logic. The results showed that the effectiveness of the proposed control strategy is much better than that of the traditional control strategy. Moreover, in high and low wind speeds, the proposed control system operates reliably and stably.
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 Control of PMSM by Sliding Mode Control and PI ControlIJMTST Journal
In order to optimize the speed-control performance of the permanent-magnet synchronous motor (PMSM)
system with different disturbances and uncertainties, a nonlinear speed-control algorithm for the PMSM servo
systems using sliding-mode control and disturbance compensation techniques is developed in this paper.
First, a sliding-mode control and PI control method based on one novel which allows chattering reduction on
control input while maintaining high tracking performance of the controller. Then, an PI control extended
sliding-mode disturbance observer is proposed to estimate lumped uncertainties directly, to compensate
strong disturbances and achieve high servo precisions. Simulation results PI control better than the SMC
control both show the validity of the proposed control approach.
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.
African vulture optimizer algorithm based vector control induction motor driv...IJECEIAES
This study describes a new optimization approach for three-phase induction motor speed drive to minimize the integral square error for speed controller and improve the dynamic speed performance. The new proposed algorithm, African vulture optimizer algorithm (AVOA) optimizes internal controller parameters of a fuzzy like proportional differential (PD) speed controller. The AVOA is notable for its ease of implementation, minimal number of design parameters, high convergence speed, and low computing burden. This study compares fuzzy-like PD speed controllers optimized with AVOA to adaptive fuzzy logic speed regulators, fuzzy-like PD optimized with genetic algorithm (GA), and proportional integral (PI) speed regulators optimized with AVOA to provide speed control for an induction motor drive system. The drive system is simulated using MATLAB/Simulink and laboratory prototype is implemented using DSP-DS1104 board. The results demonstrate that the suggested fuzzy-like PD speed controller optimized with AVOA, with a speed steady state error performance of 0.5% compared to the adaptive fuzzy logic speed regulator’s 0.7%, is the optimum alternative for speed controller. The results clarify the effectiveness of the controllers based on fuzzy like PD speed controller optimized with AVOA for each performance index as it provides lower overshoot, lowers rising time, and high dynamic response.
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.
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.
A Comparative Study of GA tuned and PSO tuned PI Controller Based Speed Contr...paperpublications3
Abstract: This paper presents a comparative study of Generic Algorithm (GA) and Partical Swarm Optimization (PSO) technique for determining the optimal parameters of (PI) controller for speed control of a brushless DC motor (BLDC) where the (BLDC) motor is modeled in simulink in MATLAB. The proposed technique was more efficient in improving the step response characteristics as well as reducing the steady-state error, rise time, settling time and maximum overshoot.
Control of Four Switch Three Phase Inverter Fed Induction Motor Drives Based ...IJPEDS-IAES
This paper presents sensorless position and speed control for a four-switch three-phase inverter (FSTPI) fed induction motor drive. Accurate knowledge of stator resistance is of utmost importance for correct operation of a number of speed sensorless induction motor control schemes in the low speed region. Since stator resistance inevitably varies with operating conditions, stable and accurate operation at near-zero speed requires an appropriate identification algorithm for the stator resistance. The paper proposes such an identification algorithm, which is developed for the rotor flux based model reference adaptive system (MRAS) type of the speed estimator in conjunction with a rotor flux oriented control scheme. In this speed estimation method only one (out of the two available) degree of freedom is utilized for speed estimation. It is utilize the second available degree of freedom as a mean for adapting the stator resistance. The parallel stator resistance and rotor speed identification algorithm is developed in a systematic manner, using Popov’s hyper stability theory. It increases the complexity of the overall control system insignificantly and enables correct speed estimation and stable drive operation at near-zero speeds. The proposed speed and position estimator with parallel stator resistance identification for FSTPI fed induction motor at very low speed under high load operation is verified by simulation and experimental results. The results show the robustness of the proposed method with FSTPI.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
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
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Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
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Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
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Charlie Greenberg, Host
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.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
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Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
Pi3426832691
1. Srujana Dabbeti, K. Vara Lakshmi / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 3, Issue 4, Jul-Aug 2013, pp.2683-2691
2683 | P a g e
Sensorless Speed Control of an Induction Motor Drive Using
Predictive Current and Torque Controllers
Srujana Dabbeti1
, K. Vara Lakshmi2
1( PG Scholar, Department of EEE, Teegala Krishna Reddy Engineering college, JNTU- Hyd, AP, INDIA
2(Assistant professor, Department of EEE, Teegala Krishna Reddy engineering college, JNTU-Hyd, AP, INDIA
ABSTRACT
This paper presents sensor less speed
control of an induction motor drive with
predictive current controller and predictive
torque control. Both the controllers do not require
measurements of the motor speed and motor flux.
A closed loop observer system with robustness
against parameters variation is used for the
control approach. The proposed observer
computes the required state variables correctly in
wide frequency range. In the system predictive
current controller based on the computation of
back electromagnetic force by the observer is
implemented. In case of motor choke use, the
choke parameters are added to predictive current
controller algorithm. It is shown that the choke
inductance has to be taken into account in
predictive controller. The predictive method is
based on examining feasible voltage vectors (VVs)
in a prescribed cost function. The VV that
minimizes the cost function is selected. A novel
robust prediction model is presented. The whole
proposed control idea makes the system
practically insensitive to the changes of motor
parameters, even at very low frequency. It is
proved that the drive system is applicable to the
high dynamic performance and wide range of
rotor speed. By using predictive torque control we
can control the ripple torque and also speed. The
obtained simulation and experimental results
confirm the good properties of the proposed speed
sensor less induction motor drive.
Keywords - Induction motor, observer, predictive
current control, predictive torque control, sensorless
drive.
I. Nomenclature
In the system description and results
presentations the per unit system is used as shown in
[3],[4].where the referenced-based values were listed.
IM – induction motor,
FOC – field oriented control,
PWM – pulse width modulation,
PCC – predictive current controller,
EMF – electromagnetic force (back EMF)
∞β– stationary frame of references,
dq – rotating frame of references,
p.u. – per unit system
com – superscript denotes commanded value,
pred – superscript denotes predicted value,
^ - denotes value calculated in the observer,
bold style font denotes vector
CEMF, C2EMF – EMF transformation matrices,
e – motor EMF,
is, ir – stator and rotor current vector,
J - inertia,
k, k-1 – instants of calculation: actual, previous, etc.,
kab - observer gain,
Lr, Ls, Lm – motor inductances,
Rr, Rs – motor resistances,
Timp - inverter switching period,
TL - load torque,
us – stator voltage vector,
φe – angle position of the motor EMF vector,
ρψs – angle position of the rotor flux vector
ωr - rotor mechanical speed,
ω2 – motor slip,
ωψr – rotor flux vector speed
Ψr, ψs- rotor and stator flux vectors.
II. Introduction
The induction motor is the most widely used
electrical motor in industrial applications. The
majority of induction machines are used in constant
speed drives, but during the last decades the
introduction of new semiconductor devices has made
variable speed drives with induction machines
available.
The work presented in this thesis is a
continuation of a work that started with studies of the
oscillatory behaviour of inverter fed induction
machines (Peterson, 1991).However, there is more to
improve in open loop drives; fast acceleration, fast
braking, fast reversal and constant speed independent
of load changes are all desirable properties of a drive
system. This requires a fast-acting and accurate
torque control in the low speed region [1].
All those properties are obtained with vector
controlled induction machines (Leonhard, 1985). The
drawback of this method is that the rotor speed of the
induction machine must be measured, which requires
a speed sensor of some kind, for example a resolver
or an incremental encoder. The cost of the speed
sensor, at least for machines with ratings less than 10
kW, is in the same range as the cost of the motor
itself. The mounting of the sensor to the motor is also
an obstacle in many applications. A sensor less
system where the speed is estimated instead of
2. Srujana Dabbeti, K. Vara Lakshmi / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 3, Issue 4, Jul-Aug 2013, pp.2683-2691
2684 | P a g e
measured would essentially reduce the cost and
complexity of the drive system. One of the main
reasons that inverter fed induction motor drives have
become popular is that any standard induction motor
can be used without modifications. Note that the term
sensor less refers to the absence of a speed sensor on
the motor shaft, and that motor currents and voltages
must still be measured. The vector control method
requires also estimation of the flux linkage of the
machine, whether the speed is estimated or not.
Research on sensor less control has been
ongoing for more than 10 years (Haemmerli, 1986
and Tamai et al, 1987), and it is remarkable that
reliable sensor less induction motor drive systems are
not readily available. The aim of the work presented
here is to derive an applicable method for sensor less
control of induction machines. The system must work
with standard induction machines and the inverter
hardware should not be considerably more complex
than present-day open loop frequency inverters.
Problems associated with sensor less control systems
have mainly included parameter sensitivity,
integrator drift, and problems at low frequencies.
Some have tried to solve these problems by
redesigning the induction machine (Jansen et al,
1994a).As it is most unfavourable using anything but
standard machines, redesigned motors are not
considered the best solution [2].
One of the mature control systems of
induction motor is the field oriented control method.
The FOC method is widely used and presents some
high standards in modern industrial drives. A
continuous trend in IM drives is to increase the
reliability of the drive system. One solution is to
decrease the amount of normally used sensors.
Because of noises and other disadvantages the
troublesome device in some of industrial drive
system is the speed sensor. Therefore, in most
modern IM drives speed sensor elimination is
required. Instead of a speed sensor, different methods
for speed calculation are proposed in the literature.
Comprehensive reviews of the IM sensor less drives
indicating that some problems with the sensor less
control are persistent, so new solutions are still
needed. Current work efforts are dedicated
particularly to zero or very low speed range or to
very high performance drives. Another problem in
electrical drives is system sensitivity to inaccuracy
and changes of motor equivalent circuit parameters.
Most of the FOC systems are very sensitive
to that inaccuracy so some parameters should be
estimated on-line. Also, robust structures of the
control and estimation schemes are generally
researched. The integral part of numerous FOC
systems is the stator current controller. Good results
of current control are reported for predictive current
based controllers. In this paper PCC is implemented
in the IM speed sensor less system with field oriented
control method. In the FOC system instead of linear
PI current controllers, predictive current controllers
may be used. The current control algorithm
previously presented was modified by using the
observer system instead of simple load model. With
such approach, better results were recorded. To avoid
the system complication for the PCC, the back EMF
calculation was integrated to flux and speed observer
for FOC IM drive.
In this paper, new results as well as the new
solution for integration of a motor choke in the
current controller are presented. The proposed drive
is speed sensor less and robust on motor parameters
changes. The obtained results confirm that the system
works properly without parameters estimation, even
in very low speed ranges. Simulation results are
presented [3].
The predictive torque control (PTC) method
is of interest as an alternative to the direct torque
control (DTC) method in applications where torque
control is more important than speed control, such as
the traction, paper, and steel industries. The PTC
method shows faster dynamic response and causes
less torque ripple compared to the DTC method
because of its characteristic, i.e., predictive control
Different kinds of PTC methods have been
investigated to date. The direct mean torque control
method was introduced to control the mean value of
the torque at a reference value .The deadbeat control
method calculates the voltage reference to achieve a
zero torque error in the next control step [4]. The
model predictive control (MPC) method determines
the optimum voltage by using the explicit model of
the motor and inverter by minimizing a cost function
[4].
In the MPC method, the criteria for voltage
selection are more flexible. If cost function
minimization is performed by the transfer function-
based controlled auto regressive integrated moving
average (CARIMA) model, the method is called
generalized predictive control. The mathematical
process is time consuming in this method. The finite
control set model predictive control (FCS-MPC)
method uses another approach to minimizing the cost
function. In this method, the discrete nature of the
power converters is contemplated. In this approach,
the feasible voltage vectors (VVs) are examined in
terms of cost and the one that minimizes the cost
function is selected
III. Proposed system
The stator field oriented control method is
used in the drive [11]. The superior PI controllers
regulate the motor speed and rotor flux. The
commanded motor current is
com
is transformed from
dq to ∞β coordinates. The PCC controls the motor
stator current in ∞β coordinates.
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Fig.1. Proposed closed loop observer system
Calculations of the PCC are synchronized
with PWM algorithm used for the inverter output
voltage generation. The inverter with PWM and PCC
works as controlled current source. The system works
without speed sensor, while only the inverter input
voltage and output currents are measured by hall-
effect sensors. Other variables required by control
system are calculated in closed-loop observer system.
1.1 Observer System
We can estimate the flux and speed by using
closed loop observer system [5].Simultaneously, the
motor EMF is calculated. The observer structure is
presented in Fig. 2.
The observer is based on the known voltage
model of the induction motor with the combination of
the rotor and stator fluxes. The stator current
relationships are presented in e.g[13]. To improve the
estimation properties, a feedback part was added. The
rotor and stator fluxes are computed as follows:
The values in (1)-(2) and consequent
relations are normalized – Appendix. The stator
magnitude, stator and rotor angle position of the flux
vectors are:
The estimated stator current vector for feedback
correction is:
Rotor mechanical speed:
Is obtained from the difference between the
motor flux synchronous speed and slip speed:
In (6) the current is
^
is determined on base of
transformed (2) equations. It can lead to obtain an
algebraic loop – if an actual and estimated currents
are determined from (2) and (6)and used in (1) the
observer correction part disappear and (1) is well
know stator voltage equation. But in real digital
control system the difference between is and is
^
continuously exists because is is last measured
sample and is
^
is estimated value for the next step of
operation. Because of that one step delay between is
and is
^
does exist. The calculation step and sequence
of (1)-(9) are significant for the observer operation.
Fig.2. Structure of the closed-loop observer.
The advantages of the stator equation (1) are
that motor speed information is not required for flux
computation. This eliminates any additional error
associated with computing or even measuring such
signals, especially at lower frequencies.
Such characteristic provides an additional
advantage of the observer and helps to extend the
stable operating point of and induction motor. It is
particularly important for extreme low frequencies,
even without additional techniques for parameters
tuning or dc drift elimination [5].
In the observer EMF is calculated as well
according to relation:
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Although a constant gain is used, it is
possible to run the controller around zero frequency
with parameter variations and without tuning
techniques. If the controllers receive commanded
torque, the drive system does not require a rotor
speed signal. Speed is only to do closed loop control.
The motor parameters appearing in the observer are
the motor inductances and the stator resistance. The
inductances have little effect on the performance,
while the stator resistance has a small effect at
frequencies close to zero.
The presented flux and speed observer has
proved to be highly insensitive against stator
resistance mismatch. This significantly extends the
stable operating region even without parameter
tuning. Rotor resistance is not included in the
observer system, so it has no noticeable effect on it;
however it is included in slip calculation.
1.2 Predictive Current Controller
The EMF was calculated using the simple
equation of the IM model. In this paper, the accuracy
of EMF calculation is improved. Better accuracy of
EMF calculation is obtained using flux and speed
closed-loop observer presented in the previous
section. The observer structure is extended in order to
calculate the EMF simultaneously with flux and
speed computation. So in PCC the EMF calculation
part is removed and substituted by the signals
obtained directly from the observer system.
The relations of the PCC are based on the
equations of the ∞β model of the IM .For PCC
derivation purposes the IM was modelled as an
inductance and EMF connected in series, while the
small motor resistance was neglected.
Stator current dynamic system is described by:
Fig.3. Used notation in PCC for switching periods.
Assuming the notation presented in Fig. 3
and for small Timp it is possible to convert (12) to the
next discrete form:
Considering (11) for period (k-1)…(k) the
known values are: commanded voltage us
com
(k-1)
and measured current is (k-1)
Other variables as is(k) and e(k-1) are unknown and
should be predicted.
In [8] the EMF value e(k-1) was simply predicted
based on known samples of e(k-2) and e(k-3) as
follows:
In this paper instead of (14)-(15) the EMF is
calculated in the flux and speed observer according to
(12) [5]. The samples of e^
(k- 2) and e^
(k- 3)
calculated by the observer are memorized and used in
the successive calculations.
The change of position of the EMF vector is:
The calculations of (15) require two arc
tangent calculations for obtaining φe (k-2) and φe (k-
2). To simplify (15) calculation of trigonometric
relation with only one arc tangent function is used:
In the IM the EMF speed changes slowly so
for small Timp it is possible to predict eˆ(k-1) by
rotating EMF vector with small ∆φe angle calculated
by (16).
The predicted value of eˆ(k-1) is:
The IM stator current sample at instant (k) is
predicted:
To optimize PCC action the minimization of
current regulation error was chosen as cost function.
The current regulation error at instant (k-1) and (k) is
as follows:
In [6] the next controller function was used:
The voltage vector us
com
(k) calculated with
(22) is applied to the minimize stator current
regulation error at (k+1).Equation (23) is based on
(11) with addition of correction part DIs:
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Fig. 4. Predictive current controller structure
1.3 Predictive Torque Controller
For application of the sensorless observer in
predictive torque control, both observer and
prediction models have to be applied without using
measured speed. When the prediction model is
applied without using measured speed, the accuracy
of the prediction can be affected by the error of
estimated speed. In order to compensate this effect, a
closed-loop prediction model is proposed [4].
Thus far, the PTC method has not been
adopted in many industrial applications because it is
implemented by means of speed sensor in most cases.
Thus, one of the main advantages of the DTC method
is not included in the PTC method. There have been
few investigations into implementing PTC without
using a speed sensor. In [4], a predictive method is
used in a neural network observer in order to estimate
the speed. Some investigations have proposed sensor
less methods for predictive current control in the
FOC method.
The main goal of PTC is direct control of
the stator flux and torque by means of a predictive
method. Predicting the stator flux and torque is based
on the induction motor and the inverter nonlinear
models that are called prediction models.
The stator flux and current prediction are
based on full order discrete model of IM in stationary
reference frame. If feedback loop is added to IM
model, uncertainties (estimated speed error,
unbalance current measurement, and parameter
variation) can be compensated. In this way,
prediction will be performed more accurately. By
using current prediction error for feedback loop, the
closed-loop prediction model will be achieved as
follows:
(26a)
(26b)
Fig. 5. Sensorless prediction model block diagram
where ψ-
sˆ¯ is the stator flux that will be attained
from observer, Vs¯ and Is¯ are the stator voltage and
current, respectively, and Rs is the stator resistance. τr
is the rotor time constant, Ls, Lr , and Lm are the
stator, rotor, and mutual inductances, respectively, ts
is the sampling interval, and σ = 1− Lm
2
/LsLr..wr
^
is
estimated rotor speed that will be gotten from
observer and Ispˆ¯ is the last predicted stator current.
Superscript ― ˆ ‖ indicates variables that are
calculated from IM model. Variables without this
superscript are measured variables. Kp1 and Kp2 are
coefficients of the sliding mode feedback for the
prediction model.
(27a)
(27b)
Assigning feedback gains will be elaborated on
later in the paper. By applying the predicted stator
flux and stator current, the next step torque can be
calculated as follows:
(28)
where T^
is the torque and p is the number of poles.
Fig. 5 shows the sensorless prediction model block
diagram.
3.4.1 Predictive Control Method.
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Cost function is a criterion for predicting the best
voltage to apply. It shows how close torque and flux
are to their set points. In this paper, FCS-MPC is
utilized in order to minimize the cost function. This
method is based on examining feasible VVs in cost
function. The VV that minimizes the cost function is
selected. Therefore, the following cost function is
calculated for each feasible VV[5]:
(29)
where Tj
^
(k + 1) and ψsj ¯ ^
(k + 1) are the predicted
torque and stator flux, which are calculated by means
of (26) and (28) considering application of jth VV.
T* and / ψ¯*/ are the torque and the flux references.
Q is a weighting factor that determines the
importance of flux control compared to torque
control. The VV which minimizes the cost function
will be chosen as the best apply. This VV has to be
exerted to the induction motor through the inverter. If
the proposed prediction model is used beside two
different kinds of observers, two sensorless predictive
control methods will be achieved.
1.4 System with Motor Choke
In some IM drives the choke is installed
between the inverter and motor terminals. The main
role of the motor choke is to limit the rate of rise of
the motor supply voltage (dv/dt). It prevents the
reflections of voltage wave which if not solved cause
over voltages.
The motor choke with series inductance has an
influence on the drive operation [6]-[7]. In some cases
the filter parameters have to be taken into account in
the control and estimation process. The same is for
motor choke.
The closed-loop observer used in the
proposed system has high robustness on system
parameters changes, but the PCC is sensitive to motor
inductance variations.
For the system with motor choke and PCC
algorithm, the motor choke inductance L1 has to be
added into all components containing σLs. So in the
PCC calculations, instead of σLs component the
substitute inductance Ls1 is used:
(30)
The simulation results shown in Fig. 6
present the PCC open loop results in case when L1 is
used and when the L1were omitted.
Fig.6. PCC action in the drive with motor choke at
100ms instant the choke inductance L1 was set to 0.
In Fig. 6, up until the100ms instant the PCC
is working correctly because L1 is taken into account
in the PCC dependencies. At 100ms instant
inductance L1 is set to 0 only in PCC equations –
without elimination of the choke in the drive. After
that the abnormal work of the system is observed.
This confirms that choke inductance has to be known
for PCC.
IV. Simulation Investigations
In the first step the PCC working without
FOC was investigated. The system was working with
motor choke. The response is shown in Fig. 7.
In Fig. 7 IM motor current magnitude was
changed from 0.5p.u. to 1p.u. The current
commanded value was obtained in 7 steps. Stator
frequency was kept constant during this test.
Fig.7. PCC operation for the IM drive with motor
choke commanded step change of stator current
magnitude.
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Fig.8. Sensorless operation motor current control in
αβ and dq references during commanded speed
changes.
In Fig. 8 motor speed changes are
commanded – decreasing and increasing. The
waveforms of the current present consistency
between commanded and actual currents
components. Proper work of the whole system is
noticeable.
V. Simulation Results
Simulation of sensor less speed control of
induction motor is done using Predictive current
control and torque control are presented
[3],[4].dynamic modelling of induction motor is taken
from [10].
Fig.9. Step change of motor frequency related to wr
20% to 30% of the motor rated mechanical speed.
Fig.10. Response of the system for the
simultaneously changes of motor parameters (runs at
5% of rated speed) – for t> 4s system is unstable (the
result of high simultaneous parameters changes).
Nominal par. are in Tab. I.
Fig. 11. Motor reversing from 10% to -10% of rated
speed under load.
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Fig. 12. Motor reversing from- 4% to 4% of rated
speed under load.
Fig. 13. Speed & Torque wave forms of Predictive
Torque Control
Fig. 14. Speed & Torque wave forms of Predictive
Torque Control with different feedback gains.
VI. Conclusions
The predictive current controller and torque
control are based on the computation of back EMF by
the observer. The whole control does not require
measurements of the motor speed and flux. The state
variables are calculated by the observer system using
only the command value of stator voltage and the
measured stator current and dc link voltage. The
whole system is practically insensitive to inaccuracy
of calculations and the deviation of motor
parameters. In case of motor choke use, the choke
parameters are added to PCC algorithm. It was shown
that the choke inductance has to be taken into account
in PCC calculations.
A novel robust sensor less prediction model
for FCS-MPC method is also proposed in this paper.
This will advance the PTC method resulting in it
becoming a superior alternative for the DTC method
in industrial applications. The obtained simulation
and experimental results confirm the good properties
of the proposed speed sensor less IM drive. The
proposed IM drive works correctly without speed
measurements even at very low speed.
In this predictive torque control method,
speed and flux is directly controlled. The speed will
be in the form of sine wave, so that higher order
harmonics can be easily eliminated.
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TABLE I
INDUCTION MOTOR DATA
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