This document analyzes the closed-loop speed control of a chopper-fed separately excited DC motor using PI controllers. It presents the modeling of a separately excited DC motor and discusses various controller types for DC motor speed control. The proposed system uses a buck converter/chopper to control the armature voltage and thereby the speed of the DC motor. PI controllers are used to generate PWM pulses for the chopper by comparing the reference and feedback speeds. Simulation and experimental results are presented to validate the closed-loop speed control using PI controllers for different load conditions.
Rotor Resistance Adaptation Scheme Using Neural Learning Algorithm for a Fuzz...IOSR Journals
This document presents a rotor resistance adaptation scheme using a neural learning algorithm for a fuzzy logic based sensorless vector control of an induction motor. It proposes using a fuzzy logic controller for speed control of the induction motor drive to provide superior transient performance compared to a PI controller. It also uses a neural network to estimate the rotor resistance online and adapt to variations caused by temperature changes. Simulation results show that the fuzzy logic controller has faster response to speed changes than the PI controller. The neural network is also able to accurately estimate changes in rotor resistance and the adapted system is robust to rotor resistance variations of up to 100%.
This document discusses indirect vector control of induction motor drives. It begins by explaining the operating principle of indirect vector control, which uses a speed feedback loop and current feedback loop. It then describes the various components of an indirect vector controlled induction motor drive system, including the speed controller, field weakening controller, vector controller, current controller, voltage source inverter, and induction motor. The vector controller computes the d-axis and q-axis stator current components to control flux and torque. The current controller matches the actual stator currents to the reference currents to provide gate signals to the voltage source inverter. Modelling and simulation of the indirect vector controlled induction motor drive using different speed controllers is then discussed.
Speed Control of Induction Motor using FOC MethodIJERA Editor
This document presents a method for speed control of induction motors using field oriented control (FOC). FOC works by controlling the flux and torque producing currents in the motor separately. It describes the FOC algorithm which involves transforming currents between stationary and rotating reference frames to allow proportional-integral control of flux and torque. Simulation results show that a PI controller provides fast, accurate speed control of an induction motor model across its full operating range with minimal overshoot. FOC allows induction motors to operate smoothly at variable speeds like DC motors and provides benefits like reduced motor size and cost.
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.
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.
This document summarizes investigations into a fuzzy logic controller for a sensorless switched reluctance motor drive. It begins by introducing switched reluctance motors and their nonlinear characteristics. It then describes designing a fuzzy logic controller to estimate rotor position with minimum steady state error and good dynamic response. The controller implementation and numerical simulation results using Matlab/Simulink are presented. Simulation results at different speeds and loads demonstrate the controller's steady state performance and ability to respond robustly under different conditions. The conclusions are that the fuzzy logic controller enables effective operation of the switched reluctance motor drive with only small errors in all tested scenarios.
An Improved Performance of Switched Reluctance Motor Drives Using Z-Source In...IOSR Journals
This document describes an improved control method for switched reluctance motor drives using a Z-source inverter with a fuzzy logic controller that has a reduced rule base. A 5x5 fuzzy logic controller is proposed to simplify the control program complexity while maintaining system performance and stability. The output scaling factor of the controller can be continuously tuned using a gain updating factor derived from fuzzy logic, which takes the system error and change in error as inputs. Simulation results on a 4-phase 6/8 pole switched reluctance motor show the effectiveness of using the Z-source inverter and reduced rule base fuzzy logic controller.
A Review on Rapid Control of a Brushless Motor in an Hybrid Systemsunil kumar
This document discusses the rapid control of a brushless motor in a hybrid system. It presents an experimental setup that uses electromagnetic clutches to allow power transfer between a brushless DC motor and an internal combustion engine via pulleys. An incremental encoder is used to measure motor angular velocity, which is fed back in a control loop to synchronize motor and engine speeds. Both classic PID control and fuzzy logic control are explored. Simulation results show that a fuzzy proportional-integral controller combined with a PID controller helps autotune gains in real-time and improves rise time and settling time compared to conventional tuning methods. The control system aims to optimize fuel efficiency in the hybrid system.
Rotor Resistance Adaptation Scheme Using Neural Learning Algorithm for a Fuzz...IOSR Journals
This document presents a rotor resistance adaptation scheme using a neural learning algorithm for a fuzzy logic based sensorless vector control of an induction motor. It proposes using a fuzzy logic controller for speed control of the induction motor drive to provide superior transient performance compared to a PI controller. It also uses a neural network to estimate the rotor resistance online and adapt to variations caused by temperature changes. Simulation results show that the fuzzy logic controller has faster response to speed changes than the PI controller. The neural network is also able to accurately estimate changes in rotor resistance and the adapted system is robust to rotor resistance variations of up to 100%.
This document discusses indirect vector control of induction motor drives. It begins by explaining the operating principle of indirect vector control, which uses a speed feedback loop and current feedback loop. It then describes the various components of an indirect vector controlled induction motor drive system, including the speed controller, field weakening controller, vector controller, current controller, voltage source inverter, and induction motor. The vector controller computes the d-axis and q-axis stator current components to control flux and torque. The current controller matches the actual stator currents to the reference currents to provide gate signals to the voltage source inverter. Modelling and simulation of the indirect vector controlled induction motor drive using different speed controllers is then discussed.
Speed Control of Induction Motor using FOC MethodIJERA Editor
This document presents a method for speed control of induction motors using field oriented control (FOC). FOC works by controlling the flux and torque producing currents in the motor separately. It describes the FOC algorithm which involves transforming currents between stationary and rotating reference frames to allow proportional-integral control of flux and torque. Simulation results show that a PI controller provides fast, accurate speed control of an induction motor model across its full operating range with minimal overshoot. FOC allows induction motors to operate smoothly at variable speeds like DC motors and provides benefits like reduced motor size and cost.
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.
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.
This document summarizes investigations into a fuzzy logic controller for a sensorless switched reluctance motor drive. It begins by introducing switched reluctance motors and their nonlinear characteristics. It then describes designing a fuzzy logic controller to estimate rotor position with minimum steady state error and good dynamic response. The controller implementation and numerical simulation results using Matlab/Simulink are presented. Simulation results at different speeds and loads demonstrate the controller's steady state performance and ability to respond robustly under different conditions. The conclusions are that the fuzzy logic controller enables effective operation of the switched reluctance motor drive with only small errors in all tested scenarios.
An Improved Performance of Switched Reluctance Motor Drives Using Z-Source In...IOSR Journals
This document describes an improved control method for switched reluctance motor drives using a Z-source inverter with a fuzzy logic controller that has a reduced rule base. A 5x5 fuzzy logic controller is proposed to simplify the control program complexity while maintaining system performance and stability. The output scaling factor of the controller can be continuously tuned using a gain updating factor derived from fuzzy logic, which takes the system error and change in error as inputs. Simulation results on a 4-phase 6/8 pole switched reluctance motor show the effectiveness of using the Z-source inverter and reduced rule base fuzzy logic controller.
A Review on Rapid Control of a Brushless Motor in an Hybrid Systemsunil kumar
This document discusses the rapid control of a brushless motor in a hybrid system. It presents an experimental setup that uses electromagnetic clutches to allow power transfer between a brushless DC motor and an internal combustion engine via pulleys. An incremental encoder is used to measure motor angular velocity, which is fed back in a control loop to synchronize motor and engine speeds. Both classic PID control and fuzzy logic control are explored. Simulation results show that a fuzzy proportional-integral controller combined with a PID controller helps autotune gains in real-time and improves rise time and settling time compared to conventional tuning methods. The control system aims to optimize fuel efficiency in the hybrid system.
Novel Method of FOC to Speed Control in Three-Phase IM under Normal and Fault...IJPEDS-IAES
This paper proposes a novel method for speed control of three-phase
induction motor (IM) which can be used for both healthy three-phase IM and
three-phase IM under open-phase fault. The proposed fault-tolerant control
system is derived from conventional field-oriented control (FOC) algorithm
with minor changes on it. The presented drive system is based on using an
appropriate transformation matrix for the stator current variables. The
presented method in this paper can be also used for speed control of singlephase
IMs with two windings. The feasibility of the proposed strategy is
verified by simulation results.
This document presents a seminar on field oriented control of induction motors. It discusses direct and indirect field oriented control, with direct being better at high speeds but indirect not requiring additional sensors. It also discusses applications in industries like pumps, fans, conveyors and elevators. The document presents Matlab simulations comparing control methods, showing fuzzy logic control has better speed and torque response than PI control, with improved performance at low speeds. It concludes the hybrid model using current estimation could improve indirect control at low speeds.
A comparative study of pi, fuzzy and hybrid pi fuzzy controller for speed con...Asoka Technologies
This paper presents the comparative study between PI, fuzzy and hybrid PI-Fuzzy controller for speed control of brushless dc (BLDC) motor. The control structure of the proposed drive system is described. The simulation results of the drive system for different operation modes are evaluated and compared. A fuzzy controller offers better speed response for start-up while PI controller has good compliance over variation of load torque but has slow settling response. Hybrid controller has an advantage of integrating a superiority of these two controllers for better control performances. Matlab/Simulink is used to carry out the simulation.
This document describes using a fuzzy logic controller and PID controller to control the speed of a DC motor. It first provides background on DC motors and controllers. It then discusses the design of a fuzzy logic controller for a DC motor, including defining the inputs, rule base, inference engine, and defuzzification method. The document presents the modeling of a separately excited DC motor. It then simulates the motor's speed response using a PID controller and fuzzy logic controller in MATLAB. The results show that the fuzzy logic controller has better transient and steady-state response than the PID controller for controlling the non-linear DC motor speed.
Brushless Dc Motor Speed Control Using Proportional-Integral And Fuzzy Contro...IOSR Journals
This document summarizes and compares proportional-integral (PI) control and fuzzy logic control for speed regulation of a permanent magnet brushless DC motor. It first provides background on brushless DC motors and reviews previous literature on speed control techniques. It then describes implementing PI control in closed loop simulations, comparing three tuning methods. Fuzzy logic control is also implemented using two inputs (speed and current errors) and simulation results are presented. Both controllers are able to regulate speed under varying load torques and reference speeds, with fuzzy logic control having better performance in terms of overshoot, settling time and speed drop compared to PI control.
This document summarizes a study that uses Takagi-Sugeno fuzzy logic control as a speed controller for indirect field oriented control of an induction motor drive. The study builds a simulation model of indirect field oriented control for an induction motor in MATLAB Simulink. Takagi-Sugeno fuzzy logic is then applied as the speed controller using error and derivative error as inputs and change of torque command as the output. Simulation results show zero overshoot, a rise time of 0.4 seconds, and a settling time of 0.4 seconds. The steady state error is 0.01% indicating the speed can accurately follow the reference speed. The fuzzy logic controller provides effective speed control for the induction motor drive.
Hybrid PI-Fuzzy Controller for Brushless DC motor speed controlIOSR Journals
1. The document describes a hybrid PI-fuzzy controller for speed control of a brushless DC motor.
2. It combines a proportional-integral controller, which performs well near steady-state, with a fuzzy logic controller, which handles transients better by reducing overshoot and oscillations.
3. By switching between the two controllers according to system conditions, the hybrid controller aims to achieve quick response during normal operation while minimizing overshoot during transients, obtaining the benefits of both.
In this paper, we first write a description of the operation of DC motors taking into account which parameters the speed depends on thereof. The PID (Proportional-Integral-Derivative) controllers are then briefly described, and then applied to the motor speed control already described , that is, as an electronic controller (PID), which is often referred to as a DC motor. The closed loop speed control of a Brush DC motor is developed applying the well-known PID control algorithm. The objective of this work is to designed and simulate a new control system to keep the speed of the DC motor constant before variations of the load (disturbances), automatically depending to the PID controller. The system was designed and implementation by using MATLAB/SIMULINK and DC motor.
This document presents a project report on simulating automatic speed control of a DC drive. It was submitted by four students to fulfill the requirements of a Bachelor of Technology degree. The report includes an introduction to the project, descriptions of the key components used including the DC motor, H-bridge, PWM, and sensors. It also provides the specifications of the components in the Simulink model, discusses the applications of the drive on different loads, and presents the simulation results. The conclusions discuss the advantages of the automatic speed control drive and potential future applications.
The aim of this paper is to prove that fuzzy logic algorithm is a suitable control technique for fast processes such as electrical machines. This theory has been experimented on different kinds of electrical machines such as stepping motors, dc motors and induction machines (with 6 phases) and the experimental results show that the proposed fuzzy logic algorithm is the most suitable control technique for electrical machines since this algorithm is not time consuming and it is also robust between plant parameters variations.
Fuzzy logic was used to improve induction motor control by developing alternative control methods to field oriented control. A fuzzy flux controller was developed using two fuzzy logic blocks, one to describe the nonlinear relationship between slip frequency and current, and another fuzzy PI controller for the outer control loop. Simulation results showed the fuzzy flux controller had almost as good performance as field oriented control, but required less development time. The fuzzy flux controller was further improved by replacing the linear PI controller with a nonlinear fuzzy PI controller, achieving even better dynamic performance while maintaining robustness.
Matrix Converter based Direct Torque Control of Induction MotorNeehar NLN
This topic falls under the area of speed control of induction motor. The using of advanced power electronic converters provides better response. In this case, a AC/AC converter is used to control the induction motor.
This document compares the switching behaviors of field oriented control (FOC) and direct torque control (DTC) for induction motors. Experimental tests using a dSpace 1103 controller board show that under no load conditions, FOC produces less torque ripple than DTC. However, the switching frequency of the inverter for a FOC controlled motor is about 75% higher than for a DTC controlled motor. Therefore, DTC may be preferable when fast dynamic performance is critical, while FOC provides better torque quality.
67.energy optimization of field oriented (1)imran shaikh
The document describes an adaptive flux search control technique to optimize the efficiency of a field oriented controlled six-phase induction motor drive. The technique adaptively changes the flux variation steps to decrease the convergence time of the search control algorithm. Simulation and experimental results show that when the proposed algorithm is run, it changes the stator flux amplitude to an optimal lower value than nominal to reduce input power without changing output power or torque, thereby improving efficiency. The adaptive flux search control is found to be faster than conventional search control techniques and effectively optimizes the efficiency of the six-phase induction motor drive.
This document describes a study on modeling and simulating a permanent magnet brushless DC (PMBLDC) motor drive system in MATLAB/Simulink. The authors develop a model of a PMBLDC motor with a 120-degree inverter system and implement closed-loop speed control using a PI controller. Simulation results confirm the validity of the model and controller. The paper examines the effects of load and inertia changes on the motor's speed performance.
Speed Control of Brushless DC Motor using Different Intelligence SchemesIRJET Journal
This document discusses speed control of a brushless DC motor using different control schemes, including an I-controller, PI-controller, and fuzzy logic controller. It first provides background on BLDC motors and their advantages over brushed DC motors. It then discusses modeling of a BLDC motor and the design of an I-controller, PI-controller, and fuzzy logic controller for speed control. Simulation results show that the fuzzy logic controller provides the best performance with minimum overshoot and settling time. A comparison table confirms that the fuzzy logic controller has the best response dynamics of the three controllers tested.
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.
Nowadays, A lot of industry requires Multi Motor System (MMS) applications such as propulsion and traction power, HEV, conveyer and air-conditioner. The Conventional arrangement for MMS usually done by cascading the motors drives which each drives has individual inverter. Part of MMS, Dual-Motor drives fed by a single inverter is being paid attention by the researchers. Dual-motor drives using a single three-leg inverter has its limitation in the case of different operating conditions and independent speed control requirement. Therefore, dual-Motor drives using a single Five-leg Inverter (FLI) was proposed for independent control for both motors. In PMSM drives, the information of the feedback speed and rotor angular position is compulsory for variable speed drives. Conventional solution is by using speed sensor which will increase size, cost, extra hardwire and feedback devices, especially for the case of dual-PMSM drives. The best solution to overcome this problem is by eliminating the usage of speed and position sensors for Dual-motor drives. This paper presents a new sensorless strategy using speed and position estimator for Independent Dual- Permanent Magnet Synchronous Machine (PMSM) drives which utilize Five-Leg Inverter (FLI). The proposed strategy is simulated using MATLAB/Simulink to evaluate the overall motor drive performance. Meanwhile the experimental set-up is connected to dSPACE 1103 Board. The experimental results demonstrate that the proposed estimator is successfully managed to control the Dual-PMSM drives for variation of speed and for different direction applications.
Speed Tracking of Field Oriented Control Permanent Magnet Synchronous Motor U...IJPEDS-IAES
The field oriented control theory and space vector pulse width modulation technique make a permanent magnet synchronous motor can achieve the performance as well as a DC motor. However, due to the nonlinearity of the permanent magnet synchronous motor drive characteristics, it is difficult to control by using conventional proportional-integral-derivative controller. By this reason in this paper an online neural network controller for the permanent magnet synchronous motor is proposed. The controller is designed to tracks variations of speed references and also during load disturbance. The effectiveness of the proposed method is verified by develop simulation model in MATLAB-simulink program. The simulation results show that the proposed controller can reduce the overshoot, settling time and rise time. It can be concluded that the performance of the controller is improved.
IRJET- A Performance of Hybrid Control in Nonlinear Dynamic Multirotor UAVIRJET Journal
This document summarizes a research paper that models and evaluates control techniques for multirotor unmanned aerial vehicles (UAVs). It begins with an abstract that outlines the paper's contributions: developing an accurate mathematical model of a multirotor UAV using Newton-Euler dynamics, developing nonlinear control algorithms based on this model, and comparing the performance of backstepping control, sliding mode control, and fuzzy logic control through simulation. The document then provides details of the multirotor dynamic model and each control approach, evaluating their ability to stabilize the system and reject disturbances. It concludes that hybrid control systems combining advantages of different methods should be considered.
This document describes using a fuzzy logic controller and PID controller to control the speed of a DC motor. It first provides background on DC motors and controllers. It then discusses the design of a fuzzy logic controller for a DC motor, including defining the inputs, rule base, inference engine, and defuzzification method. The document presents the modeling of a separately excited DC motor. It then simulates the motor's speed response using a PID controller and fuzzy logic controller in MATLAB. The results show that the fuzzy logic controller has better transient and steady-state response than the PID controller for controlling the non-linear DC motor speed.
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.
Novel Method of FOC to Speed Control in Three-Phase IM under Normal and Fault...IJPEDS-IAES
This paper proposes a novel method for speed control of three-phase
induction motor (IM) which can be used for both healthy three-phase IM and
three-phase IM under open-phase fault. The proposed fault-tolerant control
system is derived from conventional field-oriented control (FOC) algorithm
with minor changes on it. The presented drive system is based on using an
appropriate transformation matrix for the stator current variables. The
presented method in this paper can be also used for speed control of singlephase
IMs with two windings. The feasibility of the proposed strategy is
verified by simulation results.
This document presents a seminar on field oriented control of induction motors. It discusses direct and indirect field oriented control, with direct being better at high speeds but indirect not requiring additional sensors. It also discusses applications in industries like pumps, fans, conveyors and elevators. The document presents Matlab simulations comparing control methods, showing fuzzy logic control has better speed and torque response than PI control, with improved performance at low speeds. It concludes the hybrid model using current estimation could improve indirect control at low speeds.
A comparative study of pi, fuzzy and hybrid pi fuzzy controller for speed con...Asoka Technologies
This paper presents the comparative study between PI, fuzzy and hybrid PI-Fuzzy controller for speed control of brushless dc (BLDC) motor. The control structure of the proposed drive system is described. The simulation results of the drive system for different operation modes are evaluated and compared. A fuzzy controller offers better speed response for start-up while PI controller has good compliance over variation of load torque but has slow settling response. Hybrid controller has an advantage of integrating a superiority of these two controllers for better control performances. Matlab/Simulink is used to carry out the simulation.
This document describes using a fuzzy logic controller and PID controller to control the speed of a DC motor. It first provides background on DC motors and controllers. It then discusses the design of a fuzzy logic controller for a DC motor, including defining the inputs, rule base, inference engine, and defuzzification method. The document presents the modeling of a separately excited DC motor. It then simulates the motor's speed response using a PID controller and fuzzy logic controller in MATLAB. The results show that the fuzzy logic controller has better transient and steady-state response than the PID controller for controlling the non-linear DC motor speed.
Brushless Dc Motor Speed Control Using Proportional-Integral And Fuzzy Contro...IOSR Journals
This document summarizes and compares proportional-integral (PI) control and fuzzy logic control for speed regulation of a permanent magnet brushless DC motor. It first provides background on brushless DC motors and reviews previous literature on speed control techniques. It then describes implementing PI control in closed loop simulations, comparing three tuning methods. Fuzzy logic control is also implemented using two inputs (speed and current errors) and simulation results are presented. Both controllers are able to regulate speed under varying load torques and reference speeds, with fuzzy logic control having better performance in terms of overshoot, settling time and speed drop compared to PI control.
This document summarizes a study that uses Takagi-Sugeno fuzzy logic control as a speed controller for indirect field oriented control of an induction motor drive. The study builds a simulation model of indirect field oriented control for an induction motor in MATLAB Simulink. Takagi-Sugeno fuzzy logic is then applied as the speed controller using error and derivative error as inputs and change of torque command as the output. Simulation results show zero overshoot, a rise time of 0.4 seconds, and a settling time of 0.4 seconds. The steady state error is 0.01% indicating the speed can accurately follow the reference speed. The fuzzy logic controller provides effective speed control for the induction motor drive.
Hybrid PI-Fuzzy Controller for Brushless DC motor speed controlIOSR Journals
1. The document describes a hybrid PI-fuzzy controller for speed control of a brushless DC motor.
2. It combines a proportional-integral controller, which performs well near steady-state, with a fuzzy logic controller, which handles transients better by reducing overshoot and oscillations.
3. By switching between the two controllers according to system conditions, the hybrid controller aims to achieve quick response during normal operation while minimizing overshoot during transients, obtaining the benefits of both.
In this paper, we first write a description of the operation of DC motors taking into account which parameters the speed depends on thereof. The PID (Proportional-Integral-Derivative) controllers are then briefly described, and then applied to the motor speed control already described , that is, as an electronic controller (PID), which is often referred to as a DC motor. The closed loop speed control of a Brush DC motor is developed applying the well-known PID control algorithm. The objective of this work is to designed and simulate a new control system to keep the speed of the DC motor constant before variations of the load (disturbances), automatically depending to the PID controller. The system was designed and implementation by using MATLAB/SIMULINK and DC motor.
This document presents a project report on simulating automatic speed control of a DC drive. It was submitted by four students to fulfill the requirements of a Bachelor of Technology degree. The report includes an introduction to the project, descriptions of the key components used including the DC motor, H-bridge, PWM, and sensors. It also provides the specifications of the components in the Simulink model, discusses the applications of the drive on different loads, and presents the simulation results. The conclusions discuss the advantages of the automatic speed control drive and potential future applications.
The aim of this paper is to prove that fuzzy logic algorithm is a suitable control technique for fast processes such as electrical machines. This theory has been experimented on different kinds of electrical machines such as stepping motors, dc motors and induction machines (with 6 phases) and the experimental results show that the proposed fuzzy logic algorithm is the most suitable control technique for electrical machines since this algorithm is not time consuming and it is also robust between plant parameters variations.
Fuzzy logic was used to improve induction motor control by developing alternative control methods to field oriented control. A fuzzy flux controller was developed using two fuzzy logic blocks, one to describe the nonlinear relationship between slip frequency and current, and another fuzzy PI controller for the outer control loop. Simulation results showed the fuzzy flux controller had almost as good performance as field oriented control, but required less development time. The fuzzy flux controller was further improved by replacing the linear PI controller with a nonlinear fuzzy PI controller, achieving even better dynamic performance while maintaining robustness.
Matrix Converter based Direct Torque Control of Induction MotorNeehar NLN
This topic falls under the area of speed control of induction motor. The using of advanced power electronic converters provides better response. In this case, a AC/AC converter is used to control the induction motor.
This document compares the switching behaviors of field oriented control (FOC) and direct torque control (DTC) for induction motors. Experimental tests using a dSpace 1103 controller board show that under no load conditions, FOC produces less torque ripple than DTC. However, the switching frequency of the inverter for a FOC controlled motor is about 75% higher than for a DTC controlled motor. Therefore, DTC may be preferable when fast dynamic performance is critical, while FOC provides better torque quality.
67.energy optimization of field oriented (1)imran shaikh
The document describes an adaptive flux search control technique to optimize the efficiency of a field oriented controlled six-phase induction motor drive. The technique adaptively changes the flux variation steps to decrease the convergence time of the search control algorithm. Simulation and experimental results show that when the proposed algorithm is run, it changes the stator flux amplitude to an optimal lower value than nominal to reduce input power without changing output power or torque, thereby improving efficiency. The adaptive flux search control is found to be faster than conventional search control techniques and effectively optimizes the efficiency of the six-phase induction motor drive.
This document describes a study on modeling and simulating a permanent magnet brushless DC (PMBLDC) motor drive system in MATLAB/Simulink. The authors develop a model of a PMBLDC motor with a 120-degree inverter system and implement closed-loop speed control using a PI controller. Simulation results confirm the validity of the model and controller. The paper examines the effects of load and inertia changes on the motor's speed performance.
Speed Control of Brushless DC Motor using Different Intelligence SchemesIRJET Journal
This document discusses speed control of a brushless DC motor using different control schemes, including an I-controller, PI-controller, and fuzzy logic controller. It first provides background on BLDC motors and their advantages over brushed DC motors. It then discusses modeling of a BLDC motor and the design of an I-controller, PI-controller, and fuzzy logic controller for speed control. Simulation results show that the fuzzy logic controller provides the best performance with minimum overshoot and settling time. A comparison table confirms that the fuzzy logic controller has the best response dynamics of the three controllers tested.
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.
Nowadays, A lot of industry requires Multi Motor System (MMS) applications such as propulsion and traction power, HEV, conveyer and air-conditioner. The Conventional arrangement for MMS usually done by cascading the motors drives which each drives has individual inverter. Part of MMS, Dual-Motor drives fed by a single inverter is being paid attention by the researchers. Dual-motor drives using a single three-leg inverter has its limitation in the case of different operating conditions and independent speed control requirement. Therefore, dual-Motor drives using a single Five-leg Inverter (FLI) was proposed for independent control for both motors. In PMSM drives, the information of the feedback speed and rotor angular position is compulsory for variable speed drives. Conventional solution is by using speed sensor which will increase size, cost, extra hardwire and feedback devices, especially for the case of dual-PMSM drives. The best solution to overcome this problem is by eliminating the usage of speed and position sensors for Dual-motor drives. This paper presents a new sensorless strategy using speed and position estimator for Independent Dual- Permanent Magnet Synchronous Machine (PMSM) drives which utilize Five-Leg Inverter (FLI). The proposed strategy is simulated using MATLAB/Simulink to evaluate the overall motor drive performance. Meanwhile the experimental set-up is connected to dSPACE 1103 Board. The experimental results demonstrate that the proposed estimator is successfully managed to control the Dual-PMSM drives for variation of speed and for different direction applications.
Speed Tracking of Field Oriented Control Permanent Magnet Synchronous Motor U...IJPEDS-IAES
The field oriented control theory and space vector pulse width modulation technique make a permanent magnet synchronous motor can achieve the performance as well as a DC motor. However, due to the nonlinearity of the permanent magnet synchronous motor drive characteristics, it is difficult to control by using conventional proportional-integral-derivative controller. By this reason in this paper an online neural network controller for the permanent magnet synchronous motor is proposed. The controller is designed to tracks variations of speed references and also during load disturbance. The effectiveness of the proposed method is verified by develop simulation model in MATLAB-simulink program. The simulation results show that the proposed controller can reduce the overshoot, settling time and rise time. It can be concluded that the performance of the controller is improved.
IRJET- A Performance of Hybrid Control in Nonlinear Dynamic Multirotor UAVIRJET Journal
This document summarizes a research paper that models and evaluates control techniques for multirotor unmanned aerial vehicles (UAVs). It begins with an abstract that outlines the paper's contributions: developing an accurate mathematical model of a multirotor UAV using Newton-Euler dynamics, developing nonlinear control algorithms based on this model, and comparing the performance of backstepping control, sliding mode control, and fuzzy logic control through simulation. The document then provides details of the multirotor dynamic model and each control approach, evaluating their ability to stabilize the system and reject disturbances. It concludes that hybrid control systems combining advantages of different methods should be considered.
This document describes using a fuzzy logic controller and PID controller to control the speed of a DC motor. It first provides background on DC motors and controllers. It then discusses the design of a fuzzy logic controller for a DC motor, including defining the inputs, rule base, inference engine, and defuzzification method. The document presents the modeling of a separately excited DC motor. It then simulates the motor's speed response using a PID controller and fuzzy logic controller in MATLAB. The results show that the fuzzy logic controller has better transient and steady-state response than the PID controller for controlling the non-linear DC motor speed.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Fuzzy logic Technique Based Speed Control of a Permanent Magnet Brushless DC...IJMER
This document summarizes a research paper that analyzes speed control of a permanent magnet brushless DC motor using fuzzy logic techniques. It begins with an introduction to brushless DC motors and their applications. It then describes the dynamics and modeling of a brushless DC motor drive system. Next, it discusses conventional PID speed control and introduces fuzzy logic control as an alternative method. The next sections provide details on fuzzy logic controller design and simulations comparing the performance of PID and fuzzy logic controllers under different operating conditions. The conclusions indicate that the fuzzy logic controller provides better damping and disturbance rejection compared to the PID controller.
Comparison of different controllers for the improvement of Dynamic response o...IJERA Editor
This document compares different fuzzy logic controllers for improving the dynamic response of an indirect vector controlled induction motor drive. It presents a new fuzzy PI controller with scaling factors and evaluates its performance against fuzzy PI and fuzzy MRAC (model reference adaptive control) controllers. Simulation results show that the proposed fuzzy PI with scaling factors has a faster settling time than fuzzy PI, and is less complex than fuzzy MRAC while still providing good parameter insensitivity. The proposed controller provides a compromise between complexity, accuracy and settling time for induction motor applications.
This document summarizes a research paper that proposes an adaptive PID speed controller for a brushless DC motor. The paper begins with an introduction to brushless DC motors and common speed control methods like PI, PID, fuzzy logic and PWM controllers. It then discusses developing an adaptive PID controller that combines a PID controller with an auto-tuning method. This allows the controller to adapt to changing system parameters. The paper describes modeling the BLDC motor and speed control systems in MATLAB/Simulink. Simulation results are presented and analyzed to verify the adaptive PID controller's performance. The adaptive PID controller is found to improve system adaptability compared to other control methods.
Speed Control of DC Motor under Varying Load Using PID ControllerCSCJournals
DC motors are used extensively in industrial variable speed applications because of most demanding speed-torque characteristics and are simple in controlling aspects. This paper presents a DC motor speed controlling technique under varying load condition. The linear system model of separately excited DC motor with Torque-variation is designed using PID controller. A Matlab simulation of proposed system with no-Load and full-load condition is performed on Simulink platform to observe the system response. The motor speed is kept constant in this experiment. The simulation result of the experiment shows that a motor is running approximately at a constant speed regardless of a motor load. The Simulink results show that the speed of the motor is slow down only for about 270 rpm (9%) in 980 milliseconds under the effect of full load. However, the motor speed is hunting about 200 rpm (6.66%) in 900 milliseconds on unloading condition. It is concluded that a PID controller is successful tool for controlling the motor speed in presence of load disturbances.
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.
Direct Torque Control of a Bldc Motor Based on Computing TechniqueIOSR Journals
This document discusses direct torque control of a brushless DC motor using a fuzzy logic controller. It begins with an introduction to brushless DC motors and their advantages over conventional DC motors. It then discusses the mathematical modeling and operation of brushless DC motors. The document proposes using a fuzzy logic controller for speed control of the brushless DC motor. It describes the components and operation of a fuzzy logic controller, including fuzzification, a knowledge base of rules, fuzzy reasoning, and defuzzification. Simulation results are presented showing the performance of the proposed fuzzy logic controller for brushless DC motor speed control.
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.
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.
This document summarizes a research paper on using fuzzy logic to control the speed of a DC motor. It begins by describing the objectives of designing a high-current driver circuit for the motor and using an efficient fuzzy logic algorithm to accurately track motor velocity. It then provides mathematical analysis of the separately excited DC motor and describes implementing a fuzzy logic controller using FPGA. Membership functions, rule inference, and defuzzification are implemented in VHDL. Feedback is provided by an optical encoder to measure motor speed. Simulation results show the fuzzy controller can accurately control motor speed. In conclusion, the fuzzy logic approach provides an efficient and accurate method for DC motor speed control that does not require an accurate mathematical model of the motor.
Speed control of Separately Excited DC Motor using various Conventional Contr...IJERA Editor
This paper presents comparative study of various conventional controllers such as Proportional (P), Proportional
Derivative (PD), Proportional integral (PI) and Proportional Integral Derivative (PID) controller for a speed
control of a Separately Excited Direct Current (SEDC) motor by using MATLAB / SIMULINK. All controllers
have their specific function for a particular task. The speed control normally done by feedback loop or closed
loop. The aim of development of this paper is towards providing efficient and simple method for controlling the
speed. The auto - tuning method are used to for this paper to control the speed. Among all this controllers PI
controller are frequently utilized in industries as compared to PID because Derivative action are sensitive to
noise, though PID controller will improve the steady state error. Additionally it produces less overshoot,
decreasing rise time and settling time. The MATLAB simulation are analysed and compared by using the auto
tuning method.
Keywords - Proportional (P), Proportional – Derivative (PD), Proportional - Integral (PI), Proportional –
Dynamic Simulation of Induction Motor Drive using Neuro Controlleridescitation
Induction Motors are widely used in Industries, because of the low maintenance
and robustness. Speed Control of Induction motor can be obtained by maximum torque and
efficiency. Apart from other techniques Artificial Intelligence (AI) techniques, particularly
the neural networks, improves the performance & operation of induction motor drives. This
paper presents dynamic simulation of induction motor drive using neuro controller. The
integrated environment allows users to compare simulation results between conventional,
Fuzzy and Neural Network controller (NNW).The performance of fuzzy logic and artificial
neural network based controller's are compared with that of the conventional proportional
integral controller. The dynamic Modeling and Simulation of Induction motor is done using
MATLAB/SIMULINK and the dynamic performance of induction motor drive has been
analyzed for artificial intelligent controller.
Mainly the DC motors are employed in most of the application. The main objective is to Regulate the DC motor system. A motor which displays the appearances of a DC motor but there is no commutator and brushes is called as brushless DC motor. These motors are widespread to their compensations than other motors in relationships of dependability, sound, efficiency, preliminary torque and longevity. To achieve the operation more reliable and less noisy, brushless dc motors are employed. In the proposed work, dissimilar methods of speed control are analysed. In real time submission of speed control of BLDC motor, numerous strategies are executed for the speed control singularity. The modified approaches are the employment of PI controller, use of PID controller and proposed current controller.
STATOR FLUX OPTIMIZATION ON DIRECT TORQUE CONTROL WITH FUZZY LOGIC cscpconf
This document summarizes a research paper that proposes a fuzzy logic based stator flux optimization technique for direct torque control (DTC) drives. The technique uses a fuzzy logic controller to self-regulate the stator flux reference based on the torque error and initial flux value without requiring motor parameters. Simulations show the proposed fuzzy logic approach reduces torque ripple compared to conventional DTC, especially at low loads. Key advantages of the fuzzy approach include improved performance and robustness to parameter changes without motor details.
This document describes using a fuzzy logic controller to control the speed of a brushless DC motor. It begins with an abstract that outlines using a fuzzy logic algorithm to track speed references and stabilize output speed during load variations for a BLDC motor drive. It then provides background on BLDC motors and fuzzy logic control. Sections describe the operating principle and components of BLDC motors, including rotor position sensors. It also covers designing a proportional-integral (PI) speed controller as well as simulation results for PI control that show the speed and torque performance. Finally, it discusses the structure of a fuzzy logic controller, including the fuzzification and defuzzification components.
Speed Control of Brushless Dc Motor Using Fuzzy Logic Controlleriosrjce
This paper presents a control scheme of a fuzzy logic for the brushless direct current (BLDC)
permanent magnet motor drives. The mathematical model of BLDC motor and fuzzy logic algorithm is derived.
The controller is designed to tracks variations of speed references and stabilizes the output speed during load
variations. The BLDC has some advantages compare to the others type of motors, however the nonlinearity of
the BLDC motor drive characteristics, because it is difficult to handle by using conventional proportionalintegral
(PI) controller. The BLDC motor is fed from the inverter where the rotor position and current
controller is the input. In order to overcome this main problem, the fuzzy logic control is learned continuously
and gradually becomes the main effective control. The effectiveness of the proposed method is verified by
develop simulation model in MATLAB-Simulink program. The simulation results show that the proposed fuzzy
logic controller (FLC) produce significant improvement control performance compare to the PI controller for
both condition controlling speed reference variations and load disturbance variations. Fuzzy logic is introduced
in order to suppressing the chattering and enhancing the robustness of the controlled system. Fuzzy boundary
layer is developed to provide smother transition to the equivalent control. Smaller overshoot in the speed
response and much better disturbance rejecting capabilities.
This document describes the design of a PI controller to minimize speed error for a DC servo motor. It presents a mathematical model of the DC servo motor and designs a PI controller using Simulink. The PI controller gains are adjusted to minimize overshoot, rise time, settling time, and speed error when the reference input changes between 110V to 220V and 110V to 55V. Simulation results show the PI controller is effective at maintaining near zero speed error and improving transient response.
Performance analysis of Fuzzy logic based speed control of DC motorIOSR Journals
The document proposes a fuzzy logic controller to improve the speed control of a separately excited DC motor compared to a conventional PID controller. It designs fuzzy logic membership functions and rules to self-tune the parameters of a PID controller based on motor speed error and change in error. Simulation results show the fuzzy tuned PID controller achieves better dynamic and static response than a conventional PID, with less overshoot, shorter settling time, and smaller steady state error.
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.
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THE SACRIFICE HOW PRO-PALESTINE PROTESTS STUDENTS ARE SACRIFICING TO CHANGE T...indexPub
The recent surge in pro-Palestine student activism has prompted significant responses from universities, ranging from negotiations and divestment commitments to increased transparency about investments in companies supporting the war on Gaza. This activism has led to the cessation of student encampments but also highlighted the substantial sacrifices made by students, including academic disruptions and personal risks. The primary drivers of these protests are poor university administration, lack of transparency, and inadequate communication between officials and students. This study examines the profound emotional, psychological, and professional impacts on students engaged in pro-Palestine protests, focusing on Generation Z's (Gen-Z) activism dynamics. This paper explores the significant sacrifices made by these students and even the professors supporting the pro-Palestine movement, with a focus on recent global movements. Through an in-depth analysis of printed and electronic media, the study examines the impacts of these sacrifices on the academic and personal lives of those involved. The paper highlights examples from various universities, demonstrating student activism's long-term and short-term effects, including disciplinary actions, social backlash, and career implications. The researchers also explore the broader implications of student sacrifices. The findings reveal that these sacrifices are driven by a profound commitment to justice and human rights, and are influenced by the increasing availability of information, peer interactions, and personal convictions. The study also discusses the broader implications of this activism, comparing it to historical precedents and assessing its potential to influence policy and public opinion. The emotional and psychological toll on student activists is significant, but their sense of purpose and community support mitigates some of these challenges. However, the researchers call for acknowledging the broader Impact of these sacrifices on the future global movement of FreePalestine.
Beyond Degrees - Empowering the Workforce in the Context of Skills-First.pptxEduSkills OECD
Iván Bornacelly, Policy Analyst at the OECD Centre for Skills, OECD, presents at the webinar 'Tackling job market gaps with a skills-first approach' on 12 June 2024
This presentation was provided by Rebecca Benner, Ph.D., of the American Society of Anesthesiologists, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.