This document summarizes a research paper that proposes using the bat algorithm to design a speed controller for a spark ignition engine. The paper first provides background on spark ignition engines, PI controllers, and the bat algorithm. It then describes using the bat algorithm to optimize the proportional and integral gains of a PI controller for a simulated spark ignition engine model in MATLAB/SIMULINK. The objective function is to minimize the integrated time absolute error of the engine speed response. Simulation results under different speed variations and load conditions are presented and analyzed to demonstrate that the bat algorithm can enhance engine speed performance compared to a conventional PI controller.
Universal Motors (UM) are normally used for driving portable apparatus such as hand tool machines, vacuum cleaners and most domestic apparatus. The importance of UM is due to its own advantages such as high starting torque, very powerful in relation to its small size, having a variable speed; and lower cost. So, this paper focus on UM speed control under variable loading conditions. A mathematical model for UM is designed. Two controllers are proposed for controlling the motor speed, output rate controller and output reset controller. Ant Colony Optimization (ACO) is proposed for tuning the controller’s parameters due to its impact on solving different optimization problems. It possesses fast convergence, minimum algorithm parameters required, lower consecution time and give optimal results without needing large number of iterations. The results are compared and discussed accurately, which show the proposed tuning technique work well and give optimal results for both controllers.
Three phase induction motor Induction is one of the widest spread motor due to its
robustness, simple construction, no need for complex circuits for starting. With several
available speed control techniques, this paper presents a new Proportional-Integral (PI)
controller and Artificial Neural Network (ANNs) control system based on vector control
scheme. MATLAB/SIMULINK software may be used to create a 3phase induction engine
model. To achieve the effectiveness of the controller, the system is subjected to external
disturbance. Experimental results are presented and satisfied with the controller results.
Short-term wind speed forecasting system using deep learning for wind turbine...IJECEIAES
It is very important to accurately detect wind direction and speed for wind energy that is one of the essential sustainable energy sources. Studies on the wind speed forecasting are generally carried out for long-term predictions. One of the main reasons for the long-term forecasts is the correct planning of the area where the wind turbine will be built due to the high investment costs and long-term returns. Besides that, short-term forecasting is another important point for the efficient use of wind turbines. In addition to estimating only average values, making instant and dynamic short-term forecasts are necessary to control wind turbines. In this study, short-term forecasting of the changes in wind speed between 1-20 minutes using deep learning was performed. Wind speed data was obtained instantaneously from the feedback of the emulated wind turbine's generator. These dynamically changing data was used as an input of the deep learning algorithm. Each new data from the generator was used as both test and training input in the proposed approach. In this way, the model accuracy and enhancement were provided simultaneously. The proposed approach was turned into a modular independent integrated system to work in various wind turbine applications. It was observed that the system can predict wind speed dynamically with around 3% error in the applications in the test setup applications.
Autotuning of pid controller for robot arm and magnet levitation planteSAT Journals
Abstract
One of the most essential work of the control engineer is tuning of controller. Majority of the controller used in industry are of the
PID type. An auto tuning is one of the method of controller tuning in which tuning of the parameters of controller is done
automatically and possibly, without any user interaction expect from initiating the operation. Present study emphasis on the relay
based auto tuning of PID controller. An auto-tuning method is implemented based on a relay experiment to determine the ultimate
gain and the ultimate period, with which the PID parameters are obtained using the Ziegler-Nichols tuning rules. An auto tuning
of robot arm model and magnet levitation model are carried out. Performance of relay based auto tuning on the basis of integral
square error is better than artificial neural network.
Keywords: Relay auto tuning, PID, FOPDT, SOPDT, Integral square error.
Universal Motors (UM) are normally used for driving portable apparatus such as hand tool machines, vacuum cleaners and most domestic apparatus. The importance of UM is due to its own advantages such as high starting torque, very powerful in relation to its small size, having a variable speed; and lower cost. So, this paper focus on UM speed control under variable loading conditions. A mathematical model for UM is designed. Two controllers are proposed for controlling the motor speed, output rate controller and output reset controller. Ant Colony Optimization (ACO) is proposed for tuning the controller’s parameters due to its impact on solving different optimization problems. It possesses fast convergence, minimum algorithm parameters required, lower consecution time and give optimal results without needing large number of iterations. The results are compared and discussed accurately, which show the proposed tuning technique work well and give optimal results for both controllers.
Three phase induction motor Induction is one of the widest spread motor due to its
robustness, simple construction, no need for complex circuits for starting. With several
available speed control techniques, this paper presents a new Proportional-Integral (PI)
controller and Artificial Neural Network (ANNs) control system based on vector control
scheme. MATLAB/SIMULINK software may be used to create a 3phase induction engine
model. To achieve the effectiveness of the controller, the system is subjected to external
disturbance. Experimental results are presented and satisfied with the controller results.
Short-term wind speed forecasting system using deep learning for wind turbine...IJECEIAES
It is very important to accurately detect wind direction and speed for wind energy that is one of the essential sustainable energy sources. Studies on the wind speed forecasting are generally carried out for long-term predictions. One of the main reasons for the long-term forecasts is the correct planning of the area where the wind turbine will be built due to the high investment costs and long-term returns. Besides that, short-term forecasting is another important point for the efficient use of wind turbines. In addition to estimating only average values, making instant and dynamic short-term forecasts are necessary to control wind turbines. In this study, short-term forecasting of the changes in wind speed between 1-20 minutes using deep learning was performed. Wind speed data was obtained instantaneously from the feedback of the emulated wind turbine's generator. These dynamically changing data was used as an input of the deep learning algorithm. Each new data from the generator was used as both test and training input in the proposed approach. In this way, the model accuracy and enhancement were provided simultaneously. The proposed approach was turned into a modular independent integrated system to work in various wind turbine applications. It was observed that the system can predict wind speed dynamically with around 3% error in the applications in the test setup applications.
Autotuning of pid controller for robot arm and magnet levitation planteSAT Journals
Abstract
One of the most essential work of the control engineer is tuning of controller. Majority of the controller used in industry are of the
PID type. An auto tuning is one of the method of controller tuning in which tuning of the parameters of controller is done
automatically and possibly, without any user interaction expect from initiating the operation. Present study emphasis on the relay
based auto tuning of PID controller. An auto-tuning method is implemented based on a relay experiment to determine the ultimate
gain and the ultimate period, with which the PID parameters are obtained using the Ziegler-Nichols tuning rules. An auto tuning
of robot arm model and magnet levitation model are carried out. Performance of relay based auto tuning on the basis of integral
square error is better than artificial neural network.
Keywords: Relay auto tuning, PID, FOPDT, SOPDT, Integral square error.
Induction motors are work-horse of the industry and major element in energy conversion. The replacement of the existing non-adjustable speed drives with the modern variable frequency drives would save considerable amount of electricity. A proper control scheme for variable frequency drives can enhance the efficiency and performance of the drive. This paper attempt to provide a rigorous review of various control schemes for the induction motor control and provides critical analysis and guidelines for the future research work. A detailed study of sensor based control schemes and sensor-less control schemes has been investigated. The operation, advantages, and limitations of the various control schemes are highlighted and different types of optimization techniques have been suggested to overcome the limitations of control techniques.
Optimization of PID for industrial electro-hydraulic actuator using PSOGSATELKOMNIKA JOURNAL
The Electro-hydraulic actuator (EHA) systems known to be extremely nonlinear due to its dynamic
characteristics and these existing nonlinearities and uncertainties yield to the constraint in the control of EHA
system, which influences the position tracking accuracy and affect the occurrences of leakage and friction
in the system. The purpose of this work is to develop the mathematical model for the industrial
electrohydraulic actuator, then to design a controller by proportional-integral-derivative (PID) and optimize
the parameters using Particle Swarm Optimization-Gravitational Search Algorithm (PSOGSA). A few
controllers such as conventional PID (CPID) and model reference adaptive control (MRAC) designed for
comparison. The performance of PID, PID-PSOGSA and modern controller MRAC will be compared in order
to determine the most efficient controller. Despite all controllers are capable to provide good performance,
PID-PSOGSA control methods generate good response compared to PID and MRAC in term of positioning.
Electromagnetic Braking System using Ultrasonic SensorAI Publications
The concept of our paper is based on the automatic braking system. As we know that most time the accident takes place due to loss of control, drunk & drive and much more breaking reason.In our system there is a sensor that detects the speed of movement of the vehicle and an ultrasonic sensor, that sense the distance of the object in front of the vehicle. The sensor system will sense the speed of the vehicle or object in the front while the microcontroller calculates the distance required to stop the moving vehicle. The whole system is automatic and the braking application will take place without any manual input therefore it will decrease the rate of error hence the rate of road accidents.
Quadrotor control is needed so that the quadrotor can float close to the stationary state. For that we need control techniques. One control technique that can be designed and implemented in quadrotor is PID control. PID parameter tuning using the Genetic Algorithm technique can speed up the manual tuning process. The weakness in the application of the Genetic Algorithm rule is that it often rejects important information found in other individuals and causes premature convergence, especially at the beginning of the generation. These problems can be overcome by using crossover and mutation rules with different probability levels according to fitness values and evolutionary processes. The results of the study using fast genetic algorithm techniques obtained constants Kp, Ki and Kd with the lowest rise time and overshoot, namely 0.010, 0.001 and 0.036 at the pitch angle. At the roll angle, they are 0.010, 0.001 and 0.03. At yaw angle 0.018, 0.006 and 0.043. Comparison of PID tuning simulations using fast genetic algorithm with genetic algorithm standards, shows that fast genetic algorithm has increased optimum generation achievement faster by 26.67% at pitch angle, 44% at roll angle and 20% at yaw angle. This condition has an effect on increasing simulation execution time, where fast genetic algorithm is 26.4% faster at pitch angle, 38.05% at roll angle, and 24.19% at yaw angle
Control of IC Engine: Design a Novel MIMO Fuzzy Backstepping Adaptive Based F...Waqas Tariq
This paper expands a Multi Input Multi Output (MIMO) fuzzy estimator variable structure control (VSC) which controller coefficient is on-line tuned by fuzzy backstepping algorithm. The main goal is to guarantee acceptable trajectories tracking between the internal combustion engine (IC engine) air to fuel ratio and the desired input. The fuzzy controller in proposed fuzzy estimator variable structure controller is based on Lyapunov fuzzy inference system (FIS) with minimum model based rule base. The input represents the function between variable structure function, error and the rate of error. The outputs represent fuel ratio, respectively. The fuzzy backstepping methodology is on-line tune the variable structure function based on adaptive methodology. The performance of the MIMO fuzzy estimator VSC which controller coefficient is on-line tuned by fuzzy backstepping algorithm (FBAFVSC) is validated through comparison with VSC and proposed method. Simulation results signify good performance of fuel ratio in presence of uncertainty and external disturbance.
Objective functions modification of GA optimized PID controller for brushed D...IJECEIAES
PID Optimization by Genetic Algorithm or any intelligent optimization method is widely being used recently. The main issue is to select a suitable objective function based on error criteria. Original error criteria that is widely being used such as ITAE, ISE, ITSE and IAE is insufficient in enhancing some of the performance parameter. Parameter such as settling time, rise time, percentage of overshoot, and steady state error is included in the objective function. Weightage is added into these parameters based on users’ performance requirement. Based on the results, modified error criteria show improvement in all performance parameter after being modified. All of the error criteria produce 0% overshoot, 29.51%-39.44% shorter rise time, 21.11%-42.98% better settling time, 10% to 53.76% reduction in steady state error. The performance of modified objective function in minimizing the error signal is reduced. It can be concluded that modification of objective function by adding performance parameter into consideration could improve the performance of rise time, settling time, overshoot percentage, and steady state error.
Main issue in urban transportation system is traffic accident which caused by several factors where there are two factors that has a significant contribution in accident are overspeed and fatigue. Therefore, main objective of this research is to develop Speed Limiter Integrated Analyzer (SLIFA). This device will be controlling the speed by cutting off the fuel supply to the engine when driver's fatigue or speeds are beyond limitation. This research was consists of four steps which are Step 1 is study literature on types of vehicle. Step 2, detail engineering design that is focused in this research. Step 3 is describing the target of SLIFA installation. Step 4 is fabricating and testing of SLIFA on truck and bus in range of July 2017 to January 2018. The result shows the appropriate voltage for speed at 70 km/h is 10.7 volt for limiting the speed. The traffic accident has succesfully decreased up to 47% after SLIFA installed on truck and bus. It can be concluded that the SLIFA application on transportation especially on truck and bus was much recommended to reduce traffic accident and play an appropriate government regulation.
Data-based PID control of flexible joint robot using adaptive safe experiment...journalBEEI
This paper proposes the data-based PID controller of flexible joint robot based on adaptive safe experimentation dynamics (ASED) algorithm. The ASED algorithm is an enhanced version of SED algorithm where the updated tuning variable is modified to adapt to the change of the objective function. By adopting the adaptive term to the updated equation of SED, it is expected that the convergence accuracy can be further improved. The effectiveness of the ASED algorithm is verified to tune the PID controller of flexible joint robot. In this flexible joint control problem, two PID controllers are utilized to control both rotary angle tracking and vibration of flexible joint robot. The performance of the proposed data-based PID controller is assessed in terms of trajectory tracking of angular motion, vibration reduction and statistical analysis of the pre-defined control objective function. The simulation results showed that the data-based PID controller based on ASED is able to produce better control accuracy than the conventional SED based method.
Design of automatic navigation control system for agricultural vehicleeSAT Journals
Abstract The tractor automatic navigation technology is one of the hottest research fields of precision agriculture as well as a major means for realizing intelligent operating of agricultural vehicle in future. This paper presents a thorough research on GPS automatic navigation technology of agricultural vehicle considering that working conditions and field conditions for the tractor are complex and that there is a high requirement on the precision of the driving path of the tractor. Major contents of the research are as follows: The hydraulic control valve was selected by testing. A hydraulic control valve test platform specific to navigation was designed. The test platform can gather information about the flow and pressure of each measured hydraulic valve in a real-time manner. A navigation valve block was developed. Finally, the navigation valve block was used in electro-hydraulic transformation of model vehicle, realizing the control of electrical signal in tractor steering. A hardware platform for the automatic navigation system was built. A navigation controller based on ARM chip, the RTK-GPS positioning system and the angle sensor constitute the hardware platform of the autopilot system of the tractor. The hardware platform is the basis for realizing automatic navigation of the tractor. The navigation control algorithm was studied, pure pursuit model tracking algorithm were analyzed; the navigation decision-making control system based on the pure pursuit model tracking algorithm was designed; the kinematics model of the tractor was established. The pure tracking model has been simulated by MATLAB software, and the system has good stability and sensitivity. The experimental research on the automatic navigation system of the tractor was conducted. Based on the automatic navigation platform developed above, experiments on the control of the tractor walking straight at the flat road have been done. The results proved that the automatic navigation system has the capability of tracking the straight path of the tractor in a real-time and stable manner and meets the requirements of precision agriculture. Keywords: Automatic Navigation, Precision Agriculture, Steering Control System, Path Tracking
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.
Induction motors are work-horse of the industry and major element in energy conversion. The replacement of the existing non-adjustable speed drives with the modern variable frequency drives would save considerable amount of electricity. A proper control scheme for variable frequency drives can enhance the efficiency and performance of the drive. This paper attempt to provide a rigorous review of various control schemes for the induction motor control and provides critical analysis and guidelines for the future research work. A detailed study of sensor based control schemes and sensor-less control schemes has been investigated. The operation, advantages, and limitations of the various control schemes are highlighted and different types of optimization techniques have been suggested to overcome the limitations of control techniques.
Optimization of PID for industrial electro-hydraulic actuator using PSOGSATELKOMNIKA JOURNAL
The Electro-hydraulic actuator (EHA) systems known to be extremely nonlinear due to its dynamic
characteristics and these existing nonlinearities and uncertainties yield to the constraint in the control of EHA
system, which influences the position tracking accuracy and affect the occurrences of leakage and friction
in the system. The purpose of this work is to develop the mathematical model for the industrial
electrohydraulic actuator, then to design a controller by proportional-integral-derivative (PID) and optimize
the parameters using Particle Swarm Optimization-Gravitational Search Algorithm (PSOGSA). A few
controllers such as conventional PID (CPID) and model reference adaptive control (MRAC) designed for
comparison. The performance of PID, PID-PSOGSA and modern controller MRAC will be compared in order
to determine the most efficient controller. Despite all controllers are capable to provide good performance,
PID-PSOGSA control methods generate good response compared to PID and MRAC in term of positioning.
Electromagnetic Braking System using Ultrasonic SensorAI Publications
The concept of our paper is based on the automatic braking system. As we know that most time the accident takes place due to loss of control, drunk & drive and much more breaking reason.In our system there is a sensor that detects the speed of movement of the vehicle and an ultrasonic sensor, that sense the distance of the object in front of the vehicle. The sensor system will sense the speed of the vehicle or object in the front while the microcontroller calculates the distance required to stop the moving vehicle. The whole system is automatic and the braking application will take place without any manual input therefore it will decrease the rate of error hence the rate of road accidents.
Quadrotor control is needed so that the quadrotor can float close to the stationary state. For that we need control techniques. One control technique that can be designed and implemented in quadrotor is PID control. PID parameter tuning using the Genetic Algorithm technique can speed up the manual tuning process. The weakness in the application of the Genetic Algorithm rule is that it often rejects important information found in other individuals and causes premature convergence, especially at the beginning of the generation. These problems can be overcome by using crossover and mutation rules with different probability levels according to fitness values and evolutionary processes. The results of the study using fast genetic algorithm techniques obtained constants Kp, Ki and Kd with the lowest rise time and overshoot, namely 0.010, 0.001 and 0.036 at the pitch angle. At the roll angle, they are 0.010, 0.001 and 0.03. At yaw angle 0.018, 0.006 and 0.043. Comparison of PID tuning simulations using fast genetic algorithm with genetic algorithm standards, shows that fast genetic algorithm has increased optimum generation achievement faster by 26.67% at pitch angle, 44% at roll angle and 20% at yaw angle. This condition has an effect on increasing simulation execution time, where fast genetic algorithm is 26.4% faster at pitch angle, 38.05% at roll angle, and 24.19% at yaw angle
Control of IC Engine: Design a Novel MIMO Fuzzy Backstepping Adaptive Based F...Waqas Tariq
This paper expands a Multi Input Multi Output (MIMO) fuzzy estimator variable structure control (VSC) which controller coefficient is on-line tuned by fuzzy backstepping algorithm. The main goal is to guarantee acceptable trajectories tracking between the internal combustion engine (IC engine) air to fuel ratio and the desired input. The fuzzy controller in proposed fuzzy estimator variable structure controller is based on Lyapunov fuzzy inference system (FIS) with minimum model based rule base. The input represents the function between variable structure function, error and the rate of error. The outputs represent fuel ratio, respectively. The fuzzy backstepping methodology is on-line tune the variable structure function based on adaptive methodology. The performance of the MIMO fuzzy estimator VSC which controller coefficient is on-line tuned by fuzzy backstepping algorithm (FBAFVSC) is validated through comparison with VSC and proposed method. Simulation results signify good performance of fuel ratio in presence of uncertainty and external disturbance.
Objective functions modification of GA optimized PID controller for brushed D...IJECEIAES
PID Optimization by Genetic Algorithm or any intelligent optimization method is widely being used recently. The main issue is to select a suitable objective function based on error criteria. Original error criteria that is widely being used such as ITAE, ISE, ITSE and IAE is insufficient in enhancing some of the performance parameter. Parameter such as settling time, rise time, percentage of overshoot, and steady state error is included in the objective function. Weightage is added into these parameters based on users’ performance requirement. Based on the results, modified error criteria show improvement in all performance parameter after being modified. All of the error criteria produce 0% overshoot, 29.51%-39.44% shorter rise time, 21.11%-42.98% better settling time, 10% to 53.76% reduction in steady state error. The performance of modified objective function in minimizing the error signal is reduced. It can be concluded that modification of objective function by adding performance parameter into consideration could improve the performance of rise time, settling time, overshoot percentage, and steady state error.
Main issue in urban transportation system is traffic accident which caused by several factors where there are two factors that has a significant contribution in accident are overspeed and fatigue. Therefore, main objective of this research is to develop Speed Limiter Integrated Analyzer (SLIFA). This device will be controlling the speed by cutting off the fuel supply to the engine when driver's fatigue or speeds are beyond limitation. This research was consists of four steps which are Step 1 is study literature on types of vehicle. Step 2, detail engineering design that is focused in this research. Step 3 is describing the target of SLIFA installation. Step 4 is fabricating and testing of SLIFA on truck and bus in range of July 2017 to January 2018. The result shows the appropriate voltage for speed at 70 km/h is 10.7 volt for limiting the speed. The traffic accident has succesfully decreased up to 47% after SLIFA installed on truck and bus. It can be concluded that the SLIFA application on transportation especially on truck and bus was much recommended to reduce traffic accident and play an appropriate government regulation.
Data-based PID control of flexible joint robot using adaptive safe experiment...journalBEEI
This paper proposes the data-based PID controller of flexible joint robot based on adaptive safe experimentation dynamics (ASED) algorithm. The ASED algorithm is an enhanced version of SED algorithm where the updated tuning variable is modified to adapt to the change of the objective function. By adopting the adaptive term to the updated equation of SED, it is expected that the convergence accuracy can be further improved. The effectiveness of the ASED algorithm is verified to tune the PID controller of flexible joint robot. In this flexible joint control problem, two PID controllers are utilized to control both rotary angle tracking and vibration of flexible joint robot. The performance of the proposed data-based PID controller is assessed in terms of trajectory tracking of angular motion, vibration reduction and statistical analysis of the pre-defined control objective function. The simulation results showed that the data-based PID controller based on ASED is able to produce better control accuracy than the conventional SED based method.
Design of automatic navigation control system for agricultural vehicleeSAT Journals
Abstract The tractor automatic navigation technology is one of the hottest research fields of precision agriculture as well as a major means for realizing intelligent operating of agricultural vehicle in future. This paper presents a thorough research on GPS automatic navigation technology of agricultural vehicle considering that working conditions and field conditions for the tractor are complex and that there is a high requirement on the precision of the driving path of the tractor. Major contents of the research are as follows: The hydraulic control valve was selected by testing. A hydraulic control valve test platform specific to navigation was designed. The test platform can gather information about the flow and pressure of each measured hydraulic valve in a real-time manner. A navigation valve block was developed. Finally, the navigation valve block was used in electro-hydraulic transformation of model vehicle, realizing the control of electrical signal in tractor steering. A hardware platform for the automatic navigation system was built. A navigation controller based on ARM chip, the RTK-GPS positioning system and the angle sensor constitute the hardware platform of the autopilot system of the tractor. The hardware platform is the basis for realizing automatic navigation of the tractor. The navigation control algorithm was studied, pure pursuit model tracking algorithm were analyzed; the navigation decision-making control system based on the pure pursuit model tracking algorithm was designed; the kinematics model of the tractor was established. The pure tracking model has been simulated by MATLAB software, and the system has good stability and sensitivity. The experimental research on the automatic navigation system of the tractor was conducted. Based on the automatic navigation platform developed above, experiments on the control of the tractor walking straight at the flat road have been done. The results proved that the automatic navigation system has the capability of tracking the straight path of the tractor in a real-time and stable manner and meets the requirements of precision agriculture. Keywords: Automatic Navigation, Precision Agriculture, Steering Control System, Path Tracking
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.
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.
Indirect Vector Control of Induction Motor Using Pi Speed Controller and Neur...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Cuckoo search algorithm based for tunning both PI and FOPID controllers for ...IJECEIAES
Wind Energy has received great attention in this century. It influences the new power systems, adding new challenges to the power system expansion problem. Nowadays, double feed induction generator (DFIG) wind turbines are used majorly in wind farms, due to their advantages over other types. Therefore, the analysis of the system using this type has become very important. In this paper, a wind turbine modelling was introduced with suggested controllers, in order to enhance the system response, with respect to both pitch control and maximum output power. Cuckoo search algorithm (CSA), a meta-heuristic optimization technique, was implemented to determine the gains of a proportional-integral (PI) controller and fractional order proportional-integral-derivative (FOPID) controller to optimize the system, which considered three control loops: pitch, rotor-side converter, and grid-side converter control loop. Simulation results were determined using MATLAB/Simulink. The comparative analysis of the results showed that the PI Controller gave the simplest and the best response in case of the pitch and rotor-side control loops while the FOPID was the best when applied to the grid-side control loop. Based on the results and discussion, a suggestion of using a compination of each controller was introduced.
REMAPPING AND SIMULATION OF EFI SYSTEM FOR SI ENGINE USING PIGGYBACK ECUBarhm Mohamad
Electronic fuel injection (EFI) is a complex system comprising many parts, both mechanical and electronic, controlling an internal combustion engine. It carries out many different tasks. In motorsport, the most important thing to achieve is power optimisation. High power and engine responsiveness are often desired to gain a competitive edge. Usually, motorsport enthusiast will upgrade their stock vehicle with aftermarket components, such as higher rating turbo, longer duration camshafts, and exhaust system. These are difficult to carry out, time-consuming, and expensive tasks compared to the ECU calibration method. In Vietnam, most customers who want to change their vehicle's performance choose the Remap method on Factory ECU. By using the vehicle performance regulation method with a piggyback ECU, it is easier for the user to adjust the power than by the popular Remap method, the advantages being, for example, low cost and easy installation. Currently, there are very few documents describing and evaluating the effectiveness of a piggyback ECU installed in a vehicle. So, in this paper, an experimental reconstruction of an electronic fuel injection system with a piggyback ECU was performed, then the control algorithms of the electronic fuel injection system were simulated in LabVIEW, and the results were compared with the experiment, based on the simulation model of the control algorithm of the EFI system with many modes with different engine loads and speeds. The simulation results are used to evaluate the algorithm for the piggyback ECU.
This work proposes an optimization algorithm to control speed of a permanent magnet synchronous motor (PMSM) during starting and speed reversal of motor, as well as during load disturbance conditions. The objective is to minimize the integral absolute control error of the PMSM shaft speed to achieve fast and accurate speed response under load disturbance and speed reversal conditions. The maximum overshoot, peak time, settling time and rise time of the motor is also minimized to obtain efficient transient speed response. Optimum speed control of PMSM is obtained with the aid of a PID speed controller. Modified Particle Swarm Optimization (MPSO) and Ant Colony Optimization (ACO) techniques has been employed for tuning of the PID speed controller, to determine its gain coefficients (proportional, integral and derivative). Simulation results demonstrate that with use of MPSO and ACO techniques improved control performance of PMSM can be achieved in comparison to the classical Ziegler-Nichols (Z-N) method of PID tuning.
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.
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.
Permanent magnet direct current motors (PMDCM) are widely used in various applications such as space technologies, personal computers, medical, military, robotics, electrical vehicles, etc. In this paper, the mathematical model of PMDCM is designed and simulated using MATLAB software. The PMDCM speed is controlled using rate feedback controller due to its ability of improving system damping. To improve the controller performance, it’s parameters are tuned using genetic algorithm (GA) and direct search (DS) techniques. The tuning process based on different performance criteria. The most four common performance criteria used in this paper are JIAE (Integral of Absolute Error), JISE (Integral of Square Error), JITAE (Integral of Time-Weighted Absolute Error), and JITSE (Integral of Time-Weighted Square Error). The results obtained from these evolutionary techniques are compared. The results show an obvious improvement in system performance including enhancing the transient and steady state of PMDCM speed responses for all performance criteria.
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.
Hybrid controller design using gain scheduling approach for compressor systemsIJECEIAES
The automatic control system plays a crucial role in industries for controlling the process operations. The automatic control system provides a safe and proper controlling mechanism to avoid environmental and quality problems. The control system controls pressure flow, mass flow, speed control, and other process metrics and solves robustness and stability issues. In this manuscript, The Hybrid controller approach like proportional integral (PI) and proportional derivative (PD) based fuzzy logic controller (FLC) using with and without gain scheduling approach is modeled for the compressor to improve the robustness and error response control mechanism. The PI/PD-based FLC system includes step input function, the PI/PD controller, FLC with a closed-loop mechanism, and gain scheduler. The error signals and control response outputs are analyzed in detail for PI/PD-based FLC’s and compared with conventional PD/PID controllers. The PD-based FLC with the Gain scheduling approach consumes less overshoot time of 74% than the PD-based FLC without gain scheduling approach. The PD-based FLC with the gain scheduling approach produces less error response in terms of 7.9% in integral time absolute error (ITAE), 7.4% in integral absolute error (IAE), and 16% in integral square error (ISE) than PD based FLC without gain scheduling approach.
Coal-Fired Boiler Fault Prediction using Artificial Neural Networks IJECEIAES
Boiler fault is a critical issue in a coal-fired power plant due to its high temperature and high pressure characteristics. The complexity of boiler design increases the difficulty of fault investigation in a quick moment to avoid long duration shut-down. In this paper, a boiler fault prediction model is proposed using artificial neural network. The key influential parameters analysis is carried out to identify its correlation with the performance of the boiler. The prediction model is developed to achieve the least misclassification rate and mean squared error. Artificial neural network is trained using a set of boiler operational parameters. Subsequenlty, the trained model is used to validate its prediction accuracy against actual fault value from a collected real plant data. With reference to the study and test results, two set of initial weights have been tested to verify the repeatability of the correct prediction. The results show that the artificial neural network implemented is able to provide an average of above 92% prediction rate of accuracy.
COMBUSTION MONITORING THROUGH VIBRATIONAL DATA IN A TURBOCHARGED CITY CAR ENGINEIAEME Publication
Condition monitoring and optimization of diesel engine has been the focus of a
wide research approaches. Techniques have been developed in which in-cylinder
pressure measurements are used to calculate peak pressure and burn rates. In the
recent past, vibration, acoustic and speed measurements have received considerable
attention to this purpose. Methodologies have been developed in which these nonintrusive
measurements are employed to estimate the combustion progress. This work
is devoted to assess the potential application of a methodology developed by the
authors, in which the engine block vibration is used to estimate indicators able to
characterize the combustion development. Previous research activity demonstrated
that an accelerometer sensor placed in a selected position of the engine block is quite
sensitive to the combustion process in a naturally aspirated two-cylinder common rail
diesel engine mainly used in micro cars. The objective of this work is to evaluate the
applicability of the methodology to a more complex engine architecture (the same
engine was downsized by equipping it with a small turbocharger). Measurements were
performed in the engine operative field in which the turbocharger is truly effective.
The acquired signals were processed in time and frequency domains. Obtained results
proved the good accuracy of the estimation of combustion indicators (crank angle
corresponding to start of combustion, 50% of mass fraction burnt) via accelerometer
signal processing
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Developing a smart system for infant incubators using the internet of things ...IJECEIAES
This research is developing an incubator system that integrates the internet of things and artificial intelligence to improve care for premature babies. The system workflow starts with sensors that collect data from the incubator. Then, the data is sent in real-time to the internet of things (IoT) broker eclipse mosquito using the message queue telemetry transport (MQTT) protocol version 5.0. After that, the data is stored in a database for analysis using the long short-term memory network (LSTM) method and displayed in a web application using an application programming interface (API) service. Furthermore, the experimental results produce as many as 2,880 rows of data stored in the database. The correlation coefficient between the target attribute and other attributes ranges from 0.23 to 0.48. Next, several experiments were conducted to evaluate the model-predicted value on the test data. The best results are obtained using a two-layer LSTM configuration model, each with 60 neurons and a lookback setting 6. This model produces an R 2 value of 0.934, with a root mean square error (RMSE) value of 0.015 and a mean absolute error (MAE) of 0.008. In addition, the R 2 value was also evaluated for each attribute used as input, with a result of values between 0.590 and 0.845.
A review on internet of things-based stingless bee's honey production with im...IJECEIAES
Honey is produced exclusively by honeybees and stingless bees which both are well adapted to tropical and subtropical regions such as Malaysia. Stingless bees are known for producing small amounts of honey and are known for having a unique flavor profile. Problem identified that many stingless bees collapsed due to weather, temperature and environment. It is critical to understand the relationship between the production of stingless bee honey and environmental conditions to improve honey production. Thus, this paper presents a review on stingless bee's honey production and prediction modeling. About 54 previous research has been analyzed and compared in identifying the research gaps. A framework on modeling the prediction of stingless bee honey is derived. The result presents the comparison and analysis on the internet of things (IoT) monitoring systems, honey production estimation, convolution neural networks (CNNs), and automatic identification methods on bee species. It is identified based on image detection method the top best three efficiency presents CNN is at 98.67%, densely connected convolutional networks with YOLO v3 is 97.7%, and DenseNet201 convolutional networks 99.81%. This study is significant to assist the researcher in developing a model for predicting stingless honey produced by bee's output, which is important for a stable economy and food security.
A trust based secure access control using authentication mechanism for intero...IJECEIAES
The internet of things (IoT) is a revolutionary innovation in many aspects of our society including interactions, financial activity, and global security such as the military and battlefield internet. Due to the limited energy and processing capacity of network devices, security, energy consumption, compatibility, and device heterogeneity are the long-term IoT problems. As a result, energy and security are critical for data transmission across edge and IoT networks. Existing IoT interoperability techniques need more computation time, have unreliable authentication mechanisms that break easily, lose data easily, and have low confidentiality. In this paper, a key agreement protocol-based authentication mechanism for IoT devices is offered as a solution to this issue. This system makes use of information exchange, which must be secured to prevent access by unauthorized users. Using a compact contiki/cooja simulator, the performance and design of the suggested framework are validated. The simulation findings are evaluated based on detection of malicious nodes after 60 minutes of simulation. The suggested trust method, which is based on privacy access control, reduced packet loss ratio to 0.32%, consumed 0.39% power, and had the greatest average residual energy of 0.99 mJoules at 10 nodes.
Fuzzy linear programming with the intuitionistic polygonal fuzzy numbersIJECEIAES
In real world applications, data are subject to ambiguity due to several factors; fuzzy sets and fuzzy numbers propose a great tool to model such ambiguity. In case of hesitation, the complement of a membership value in fuzzy numbers can be different from the non-membership value, in which case we can model using intuitionistic fuzzy numbers as they provide flexibility by defining both a membership and a non-membership functions. In this article, we consider the intuitionistic fuzzy linear programming problem with intuitionistic polygonal fuzzy numbers, which is a generalization of the previous polygonal fuzzy numbers found in the literature. We present a modification of the simplex method that can be used to solve any general intuitionistic fuzzy linear programming problem after approximating the problem by an intuitionistic polygonal fuzzy number with n edges. This method is given in a simple tableau formulation, and then applied on numerical examples for clarity.
The performance of artificial intelligence in prostate magnetic resonance im...IJECEIAES
Prostate cancer is the predominant form of cancer observed in men worldwide. The application of magnetic resonance imaging (MRI) as a guidance tool for conducting biopsies has been established as a reliable and well-established approach in the diagnosis of prostate cancer. The diagnostic performance of MRI-guided prostate cancer diagnosis exhibits significant heterogeneity due to the intricate and multi-step nature of the diagnostic pathway. The development of artificial intelligence (AI) models, specifically through the utilization of machine learning techniques such as deep learning, is assuming an increasingly significant role in the field of radiology. In the realm of prostate MRI, a considerable body of literature has been dedicated to the development of various AI algorithms. These algorithms have been specifically designed for tasks such as prostate segmentation, lesion identification, and classification. The overarching objective of these endeavors is to enhance diagnostic performance and foster greater agreement among different observers within MRI scans for the prostate. This review article aims to provide a concise overview of the application of AI in the field of radiology, with a specific focus on its utilization in prostate MRI.
Seizure stage detection of epileptic seizure using convolutional neural networksIJECEIAES
According to the World Health Organization (WHO), seventy million individuals worldwide suffer from epilepsy, a neurological disorder. While electroencephalography (EEG) is crucial for diagnosing epilepsy and monitoring the brain activity of epilepsy patients, it requires a specialist to examine all EEG recordings to find epileptic behavior. This procedure needs an experienced doctor, and a precise epilepsy diagnosis is crucial for appropriate treatment. To identify epileptic seizures, this study employed a convolutional neural network (CNN) based on raw scalp EEG signals to discriminate between preictal, ictal, postictal, and interictal segments. The possibility of these characteristics is explored by examining how well timedomain signals work in the detection of epileptic signals using intracranial Freiburg Hospital (FH), scalp Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) databases, and Temple University Hospital (TUH) EEG. To test the viability of this approach, two types of experiments were carried out. Firstly, binary class classification (preictal, ictal, postictal each versus interictal) and four-class classification (interictal versus preictal versus ictal versus postictal). The average accuracy for stage detection using CHB-MIT database was 84.4%, while the Freiburg database's time-domain signals had an accuracy of 79.7% and the highest accuracy of 94.02% for classification in the TUH EEG database when comparing interictal stage to preictal stage.
Analysis of driving style using self-organizing maps to analyze driver behaviorIJECEIAES
Modern life is strongly associated with the use of cars, but the increase in acceleration speeds and their maneuverability leads to a dangerous driving style for some drivers. In these conditions, the development of a method that allows you to track the behavior of the driver is relevant. The article provides an overview of existing methods and models for assessing the functioning of motor vehicles and driver behavior. Based on this, a combined algorithm for recognizing driving style is proposed. To do this, a set of input data was formed, including 20 descriptive features: About the environment, the driver's behavior and the characteristics of the functioning of the car, collected using OBD II. The generated data set is sent to the Kohonen network, where clustering is performed according to driving style and degree of danger. Getting the driving characteristics into a particular cluster allows you to switch to the private indicators of an individual driver and considering individual driving characteristics. The application of the method allows you to identify potentially dangerous driving styles that can prevent accidents.
Hyperspectral object classification using hybrid spectral-spatial fusion and ...IJECEIAES
Because of its spectral-spatial and temporal resolution of greater areas, hyperspectral imaging (HSI) has found widespread application in the field of object classification. The HSI is typically used to accurately determine an object's physical characteristics as well as to locate related objects with appropriate spectral fingerprints. As a result, the HSI has been extensively applied to object identification in several fields, including surveillance, agricultural monitoring, environmental research, and precision agriculture. However, because of their enormous size, objects require a lot of time to classify; for this reason, both spectral and spatial feature fusion have been completed. The existing classification strategy leads to increased misclassification, and the feature fusion method is unable to preserve semantic object inherent features; This study addresses the research difficulties by introducing a hybrid spectral-spatial fusion (HSSF) technique to minimize feature size while maintaining object intrinsic qualities; Lastly, a soft-margins kernel is proposed for multi-layer deep support vector machine (MLDSVM) to reduce misclassification. The standard Indian pines dataset is used for the experiment, and the outcome demonstrates that the HSSF-MLDSVM model performs substantially better in terms of accuracy and Kappa coefficient.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
The A318, A319, A320 and A321 are twin-engine subsonic medium range aircraft.
The family offers a choice of engines
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
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Design of spark ignition engine speed control using bat algorithm
1. International Journal of Electrical and Computer Engineering (IJECE)
Vol. 11, No. 1, February 2021, pp. 794~801
ISSN: 2088-8708, DOI: 10.11591/ijece.v11i1.pp794-801 794
Journal homepage: http://ijece.iaescore.com
Design of spark ignition engine speed control using
bat algorithm
Herlambang Setiadi1
, Karl O. Jones2
, Teguh Aryo Nugroho3
,
Muhammad Abdillah4
, Herri Trilaksana5
, Tahta Amrillah6
1,6
School of Advanced Technology and Multidiciplinary, Universitas Airlangga, Indonesia
2
Department of Electronics and Electrical Engineering, Liverpool John Moores University, United Kingdom
3,4
Department of Electrical Engineering, Universitas Pertamina, Indonesia
5
Department of Physics, Faculty of Science and Technology, Universitas Airlangga, Indonesia
Article Info ABSTRACT
Article history:
Received Jun 11, 2020
Revised Jul 19, 2020
Accepted Jul 28, 2020
The most common problem in spark ignition engine is how to increase
the speed performance. Commonly researchers used traditional mathematical
approaches for designing speed controller of spark ignition engine. However,
this solution may not be sufficient. Hence, it is important to design the speed
controller using smart methods. This paper proposes a method for designing
speed controller of a spark ignition engine using the bat algorithm (BA).
The simulation is carried out using the MATLAB/SIMULINK environment.
Time domain simulation is carried out to investigate the efficacy of
the proposed method. From the simulation results, it is found that by
designing speed controller of spark ignition engine using PI based bat
algorithm, the speed performance of spark ignition engine can be enhanced
both in no load condition and load condition compared to conventional PI
controler.
Keywords:
Bat algorithm
Load torque
PI controller
Spark ignition engine
Speed response
Transportation services This is an open access article under the CC BY-SA license.
Corresponding Author:
Herlambang Setiadi,
School of Advanced Technology and Multidiciplinary,
Universitas Airlangga,
Campus C UNAIR Gedung Nanizar, Mulyorejo, Surabaya, Indonesia.
Email: h.setiadi@stmm.unair.ac.id
1. INTRODUCTION
Spark ignition engine is one type of ignition engine that is widely used in motor vehicles around
the world. Along with development of technology, research and development of this machine continues to be
carried out starting from the construction of the machine to its management electronics. The most frequently
discussed problems in spark ignition engines are engine performance and fuel efficiency. In engine
performance, researchers focused on controlling the engine speed and manifold pressure as reported in [1, 2].
In that research, the authors are focused on designing the engine speed controller using a traditional
mathematical approach. However, using a traditional mathematical approach may not be sufficient as
the spark ignition engine model includes high non linearity. Hence, it is essential to design the engine speed
controller based on smart methods such as using artificial intelligence methods.
Artificial intelligence methods are divided into three category: artificial neural network, fuzzy logic,
and nature inspired metaheuristic algorithms. Nature inspired metaheuristic algorithms have gained
significant attention as they could provide optimal and efficient ways for handling engineering problems.
The application of a metaheuristic algorithm on power system problems is reported in [3]. In that research,
the differential evolution algorithm was used to design the resilient wide area oscillation damping. From that
2. Int J Elec & Comp Eng ISSN: 2088-8708
Design of spark ignition engine speed control using bat algorithm (Herlambang Setiadi)
795
research, it was reported that the differential evolution algorithm provided satisfactory results in optimizing
resilient wide-area oscillation damping. Research effort in [4] attempted to use particle swarm optimization
for workflow scheduling. From their research it was found that workflow scheduling can be set optimally by
using particle swarm optimization. Authors in [5], proposed a solution for making optimal itinerary using ant
colony optimization. The application of hybrid particle swarm optimization (PSO) and weed optimization
(WO) for designing PID controller of marine diesel engine speed control is reported in [6]. From
the simulation results, it is found that by combining between PSO and WO the PID controller can be
designed optimally. Research effort in [7] explained the application of adaptive safe experimentation
dynamics for data-driven neuroendocrine-PID control of multi input multi output. Authors on [8], proposed
a method for designing PID controller tuning based on safe experimentation on liquid slosh. The application
of ant colony optimization nelder mead (ACO-NM) for designing PI controller is reported in [9]. In those
research off-road electric vehicle is used as the test bed system. From the results, it this found that by
designing PI controller based on the ACO-NM algorithm could achive the maximum overshoot average
<10%. Furthermore, ACO-NM algorithm could provide high quality solutions for lower computational cost.
A genetic algorithm was used to detect the network intrusions [10]. An attempt to use firefly
algorithm for placing reactive power compensation in distribution network is reported in [11]. From
the results, it is found that by using firefly algorithm as a method, the balance between active and reactive
power in distribution network. Among numerous types of nature inspired metaheuristic algorithms, the bat
algorithm is becoming favorable due to its simple coding and fast computational process [12]. Hence, this
paper proposes a method for optimally design speed controller of spark ignition engine using bat algorithm
(BA) as BA can provide a low computational cost and reliable results. The rest of the paper is organized as
follows: Section 2 provides the fundamental theory of spark ignition engine, PI controller and bat algorithm.
The method for designing spark ignition engine using bat algorithm is presented in Section 3. Section 4
focuses on analyzing the simulation results. The last section highlight the contribution, conclusions and
future direction of the research.
2. FUNDAMENTAL THEORY
2.1. Spark ignition engine
To simulate four-cylinder spark ignition engine, the most important part is capturing the dynamic of
each component in the system. This dynamic can be captured through mathematical representation. The first
component of the system is the throttle body. In this paper the angle of the throttle plate is the control input.
The mathematical representation of throttle body can be described using (1)-(3) [13-17].
ai m
m f g P
(1)
2 3
( ) 2.821 0.0523 0.10299 0.00063
f
(2)
2
2
1,
2
2
( ) ,
2
2
, 2
1, 2
amb
m
amb
m m amb m m amb
amb
m amb amb amb m amb
m
m amb
P
P
P
g P P P P P P
P
P P P P P P
P
P P
(3)
Where mai, θ, Pm, and Pamb are mass flow rate into manifold, throttle angle, manifold pressure and
ambient pressure. The next dynamic is intake manifold of spark ignition engine. This dynamic is very similar
to manifold pressure. The difference is in the incoming and outgoing mass flow rates representing the net rate
of change of air mass with respect to time. The mathematical representation of intake manifold can be
described using (4) [13-17].
3. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 11, No. 1, February 2021 : 794 - 801
796
0
m ai a
m
RT
P m m
V
(4)
In (4), R, T, Vm, and ma0 are specific gas constant, temperature, manifold volume, and mass flow rate
of air out of manifold pressure. The mass flow rate itself is a function of the engine speed and manifold
pressure as described in (5). The final dynamic model for simulating spark ignition engine is the torque
developed by the engine. The torque produced by the engine depends upon the engine speed, the spark
advance, mass of the air charge and the air/fuel mixture ratio. The mathematical representation of torque of
engine can be described using (5) [13-17].
2 2
2 2
181.3 379.36 21.91 / 0.85 / 0.26 0.0028
0.027 0.000107 0.00048 2.55 0.05
eng a
a a
Torque m A F A F
N N N m m
(5)
In (5), ma and A/F are mass of air in cylinder for combustion and air fuel ration. While ϑ and
Torqueeng are spark advance and torque produced by the engine. Furthermore, the engine speed of spark
ignition engine can be described using (6), where J and N are moment of inertia and engine speed [13-17].
eng load
Torque Torque
N
J
(6)
2.2. PI controller
In the control system domain, there are many ways to control a system, one way is by using
a proportional and integral controller. Each controller structure has its own advantages and disadvantages.
A proportional controller has an advantage in making the system have a faster rise time. While integral
control has the advantages of reducing the error of the system. By combining both type of controller,
the system will have faster rise time and smaller error compared to the other systems without proportional
and integral control. Usually this controller is called a PI controller [18, 19].
The output of a proportional controller is the multiplication between an error value and
the proportional gain. The proportional gain cannot be entered randomly as it has certain value limits.
The system will not reach the steady state condition if the proportional gain value is too high. Furthermore,
the system will have steady state value different with the set point if proportional gain is too low. Hence, it is
crucial to set the proportional gain controller optimally. The integral controller can be used to reduce the error
of the system response by using integration procedure on the error signal. The integral controller can be also used
to speed up time in eliminating offsets. Figure 1 shows the block diagram of a PI controller [18, 19].
+
-
input
Output
p
i
1
K e t dt
T
E(s)
+
p
K
+
Feedback
Figure 1. Block diagram of a PI controller [19, 20]
2.3. Bat algorithm
In 2010, Dr Xin She Yang from Cambridge University introduced a new type of metaheuristic
algorithm called bat algorithm. The bat algorithm was developed by analyzing the behavior of bats finding
their prey. Bats use some kind of sonar signals called echolocation to locate their nest, detect food, and avoid
obstacles in the dark (bats are nocturnal animals, and so are active at night). To use the behavior of bats for
4. Int J Elec & Comp Eng ISSN: 2088-8708
Design of spark ignition engine speed control using bat algorithm (Herlambang Setiadi)
797
solving optimization problems, describing the bats activity via mathematical representation is crucial.
The mathematical representation of bat position and velocity can be described as (7), (8) and (9) [21-23].
min max min
i
f f f f
(7)
1 *
t t t
i i i i
v v x x f
(8)
1
t t t
i i i
x x v
(9)
In (7) and (8), the optimal location of the whole solution and random vector taken from a uniform
distribution are presented as x* and β. Furthermore, the velocity of the bats can be increased by multiplying λi
and fi. Hence, λi and fi can be used to adjust the velocity of the bats. Moreover, the value of fmin and fmax are set
depending on user requirements (generally, the values are 0 and 1) [21-23].
The pulse and noise level (Ai) from bats are updated in each iteration. Furthermore, the noise level
of bats are decreased when bats find their prey. The user can choose the value of maximum and minimum
noise. For simplicity, the minimum and maximum value of noise can be set to 0 and 1 assuming that noise
level becomes 0 when bats stop emitting sound (because the bats have already found their prey). This activity
can be modeled by the mathematical representation in (10) and (11) [21-23].
1
t t
i i
A A
(10)
1 0
1 exp
t
i i
r r t
(11)
Pulse emission and a constant value in (10) and (11) are presented as ri, α and γ. For every 0< α <1
and γ>0, the mathematical representation can be described in (12). The value of α and γ can be set with
the same value between 0 to 1, for simplicity. In this paper bat position is described as the PI controller
parameters [21-23].
0
0, , ~
t t
i i i
A r r t
(12)
3. METHOD
In this section, the procedure of designing speed control of spark ignition engine is explained.
The system is simulated using the MATLAB/SIMULINK environment. Moreover, the objective of the bat
algorithm is to reduce the engine speed of the spark ignition engine. The mathematical representation of
the bat algorithm objective function is described using (13) [24-26]. With e, t, Kp, Ki are error of
the investigated signal, time, proportional controller gain and integral controller gain.
0
time
t e t dt
ITAE
(13)
Subject to:
min max
p p p
K K K
(14)
min max
i i i
K K K
(15)
The procedure of designing a PI controller for spark ignition engine speed controller based on
the bat algorithm includes the following steps:
Step 1. Input parameter of the bat algorithm and dynamic data of spark ignition engine.
Step 2. Start the bat algorithm by initializing the number of bats (population), pulse emission rate, loudness
and frequency.
Step 3. Generate the random position of the bats.
Step 4. Evaluate the objective function of each bat’s position using (13).
Step 5. Move the bats using (7), (8) and (9).
5. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 11, No. 1, February 2021 : 794 - 801
798
Step 6. If random value is smaller than noise level and if new frequency is smaller than the old frequency,
store the solution and update the loudness and pulse rate.
Step 7. Evaluate the objective function of new population using (13).
Step 8. If random value is smaller than noise level and if new frequency is smaller than old frequency, store
the solution and update the loudness and pulse rate.
Step 9. Rank the bats and obtain the best solution.
Step 10. If the termination criteria is satisfied then proceed to step 11, otherwise return to step 5.
Step 11. Apply the best position of bats Kp(s) and Ki(s) in the PI controller.
Step 12. Print the results (PI controller value).
4. RESULTS AND ANALYSIS
In this section, two different case studies are carried out to investigate the efficacy of the proposed
method (PI controller design based on the bat algorithm). The first case study, is to test the system under
different speed variation. The second case study is focused on system performance under load conditions.
Furthermore, two scenarios are considered in this paper. The first scenario is a traditional speed controller
using a PI controller. While the second scenario is the proposed method on this paper (PI controller design based
on the bat algorithm). Furthermore, Table 1 shows the optimal PI parameter based on the bat algorithm.
Table 1. Optimum parameters values obtained using bat algorithm
Variable Value
Kp 0.07199
Ki 0.06089
4.1. Speed reference variation
In the first case study, the performance of the system is tested against speed reference variation.
For the start, the speed reference is set at 3000 rpm. After 5 seconds, the speed reference is changed from
3000 rpm to 6000 rpm. It should be noted that in this case study, no disturbances are considered. Figure 2
shows the spark ignition engine speed response owing to the speed reference variation. It is noted that system
with a conventional PI controller experiences higher overshoot and slower settling time. It should be noted
that the conventional PI controller design is using PI tuner application in MATLAB/SIMULINK.
Furthermore, when the PI controller is tuned using bat algorithm, the speed response of spark ignition engine
is better than a conventional PI controller. This is indicated by the smaller overshoot and faster settling time.
This happens because the PI controller based on the bat algorithm provides optimal control signal for
the throttle. Furthermore, Tables 2 and 3 illustrate the detailed features of Figure 2.
Figure 2. Spark ignition engine speed response
Table 2. Detailed features of spark ignition engine speed response 3000 rpm
Variable PI controller PI-BA
Overshoot (rpm) 288 224
Settling time (second) 3.72 3.54
0 2 4 6 8 10
2000
3000
4000
5000
6000
7000
T (s)
Speed
Deviation(rpm)
PI-BA
PI Conventional
6. Int J Elec & Comp Eng ISSN: 2088-8708
Design of spark ignition engine speed control using bat algorithm (Herlambang Setiadi)
799
Table 3. Detailed features of spark ignition engine speed response 6000 rpm
Variable PI controller PI-BA
Overshoot (rpm) 319 18
Settling time (second) 3.89 3.66
4.2. Drag torque variation
In this section, the drag torque variation is considered to determine the impact of drag torque in
speed performance of spark ignition engine. The drag torque was first set at 25 N/m, then between 2 seconds
and 8 seconds the drag torque is set at 20 N/m, after that the drag torque is once again set at 25 N/m. Figure 3
depicts the spark ignition engine speed response due to drag torque variation. It is observed that by using PI
controller based on bat algorithm, the speed performance of the spark ignition engine is better than using
a conventional PI controller. This is indicated by the small overshoot and fast settling time of the spark
ignition engine speed response.
Figure 3. Spark ignition engine speed response due to drag torque
4.3. Control system index measurement
In this section, the spark ignition engine speed response is assessed by using ITAE, IAE and ISE.
The best performance of the spark ignition speed response is indicated by the minimum value of IAE,
ISE and ITAE. Table 4 shows the ITAE, IAE and ISE for the system without drag torque variation. While
Table 5 illustrates the ITAE, IAE and ISE with drag torque variation. It is noticeable that for both condition
the proposed method (design PI controller based on bat algorithm) provides the best results on ITAE, IAE
and ISE assessment. The mathematical representation of ITAE, IAE and ISE are described in appendix.
Table 4. ITAE, IAE and ISE performance assesement without load
Variable PI-BA PI controller
ITAE 2.567x105
2.598x105
IAE 4.389x104
4.439x104
ISE 2.139x108
2.198x108
Table 5. ITAE, IAE and ISE performance assesement with load
Variable PI-BA PI controller
ITAE 2.559x105
2.597x105
IAE 4.339x104
4.412x104
ISE 2.108x108
2.186x108
5. CONCLUSION
This paper proposed an optimal design of PI controller based on the bat algorithm for speed
controller of spark ignition engine. From the case study, 1) It is noted that PI controller can be used to control
the throttle of spark ignition engine to produce appropriate speed response. 2) It is noticeable that by
designing a PI controller using the bat algorithm, the speed response of the spark ignition engine can
0 2 4 6 8 10
2000
3000
4000
5000
6000
7000
T (s)
Speed
Deviation(rpm)
PI-BA
PIConventional
7. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 11, No. 1, February 2021 : 794 - 801
800
be enhanced. Further research is required to investigate the fuel consumption comparison between system
with smart controller and using conventional controller. Furthermore, the controller can also be designed by
using fuzzy and adaptive to speed reference and load variation.
APPENDIX
- Measuring system performance
To measure the controller performance, some indices can be used. Thypically, integral squared error
(ISE) and integral absolute error (IAE) are used as the indices for assesing the system performance [23-25].
Furthermore, for assesing the system more comprehensive, a indices that also considering time in
the calculation is designed. This indices is called as integral time absolute error (ITAE). Hence, for this paper
all of the indices (IAE, ISE and ITAE) are used to thoroughly investigate the system performance. Those
indices can be modeled as mathematical representation as described in (7)-(9) [27-29].
0
time
e t dt
IAE
(16)
2
0
time
e t dt
ISE
(17)
0
time
t e t dt
ITAE
(18)
ACKNOWLEDMENT
The corresponding author would like to thanks to Universitas Airlangga for funding this research
through “Riset Kolaborasi Mitra Luar Negeri” grant.
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