The Experts below are selected from a list of 84 Experts worldwide ranked by ideXlab platform
Hossain Altab - One of the best experts on this subject based on the ideXlab platform.
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Intelligent air-Cushion tracked vehicle performance investigation: neural-networks
'Inderscience Publishers', 2012Co-Authors: Hossain Altab, Rahman, Mohammed Ataur, Mohiuddin A. K. M., Ramesh SinghAbstract:The Intelligent Air-Cushion Tracked Vehicle (IACTV) is given focus as an alternative to conventional off-road vehicles, which are driven by track and air-Cushion systems. To make the IACTV as effi cient as possible, proper investigation of the vehicle’s performance is essential. The most relevant factors that affect the competitive effi ciency of the (ACTV) are the Tractive Effort (TE), Motion Resistance (MR) and Power Consumption (PC). Therefore, an Artifi cial Neural-Network (ANN) model is proposed to investigate the vehicle’s performance. Cushion Clearance Height (CH), and Air-Cushion Pressure (CP)are used at the input layers, while PC, TE and MR are used at the output layers. Experiments are carried out in the fi eld to investigate the vehicle’s performance, and the fi ndings are compared with the results obtained from ANN
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Nonlinear controller of an air-Cushion system for a swamp terrain vehicle: fuzzy logic approach
Professional Engineering Publishing, 2011Co-Authors: Hossain Altab, Rahman, Mohammed Ataur, Mohiuddin A. K. M.Abstract:This paper presents the fuzzy logic controller (FLC) of an air-Cushion system for a swamp peat terrain vehicle and describes the process by which it functions. Cushion Pressure is controlled by an electronic proportional control valve and FLC using the output signal of the distance (height) measuring sensor that was attached to the vehicle. The main purpose of this study was to develop a control scheme for an air-Cushion system and to investigate the relationship between vehicle vertical position and the air-Cushion system, and to illustrate the important role of the fuzzy logic control system. Experimental values were recorded in the laboratory for control system testing, and in the swamp peat terrain field for vehicle performance investigation. In this paper, a fuzzy logic expert system (FLES) model, based on the Mamdani approach, was developed to predict the changes in flowrate. The mean relative error of actual and predicted values from the FLES model of lowrate was found to be slightly above the acceptable limit. The goodness of fit of the prediction values from the FLES model was found to be close to 1.0 as expected, and hence demonstrated the good performance of the developed system
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Intelligent air-Cushion tracked vehicle performance investigation: neural-networks
'Inderscience Publishers', 2011Co-Authors: Rahman, Mohammed Ataur, Hossain AltabAbstract:Intelligent air-Cushion tracked vehicle (IACTV) is focused for the alternatives to conventional off-road vehicles, which are driven by track system and air-Cushion system. To make IACTV as efficient as possible, proper investigation of vehicle performance is essential. However, most relevant factors that affect the competitive efficiency of the air-Cushion tracked vehicle are the tractive effort, motion resistance and power consumption. Therefore, an artificial neural-network (ANN) model is proposed to investigate the vehicle performance. Cushion clearance height (CH), and air-Cushion Pressure (CP) are used at the input layers while power consumption (PC), tractive effort (TE) and motion resistance (MR) are used at the output layers. Experiments are carried out in the field to investigate the vehicle performance and compared with the results obtained from ANN
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Development of an intelligent air-Cushion system for a swamp tracked vehicle
2010Co-Authors: Hossain Altab, Rahman, Mohammed Ataur, Mohiuddin A. K. M., Aminanda Yulfian, Muhidin ArifinAbstract:This paper describes the unique structure of an intelligent air –Cushion system for an intelligent air-Cushion track vehicle (IACTV) working on swamp terrain and its performance. Based on the total motion resistance and driving force analyzing for IACTV, the load distribution for the intelligent air-Cushion system and propulsion system are investigated respectively for minimizing the total power consumption. Two main issues are studied in this paper. First, a theoretical model is developed for optimizing total power consumption of the vehicle and the effects of load distribution on vehicle tractive effort and motion resistance. Secondly, the vehicle has the ability to response for the changeable Cushion Pressure based on the clearance height. The system is effective to control the intelligent air –Cushion system with measuring the vehicle tractive effort (TE), motion resistance (MR), power consumption (PC), Cushion clearance height (CH) and Cushion Pressure (CP). Ultrasonic displacement sensor, pull-in solenoid electromagnetic switch, Pressure control sensor, micro controller, and battery pH sensor are incorporated with the Fuzzy logic controller to investigate experimentally the TE, MR, PC, CH, and CP. Experiment and simulation results showed that the optimal power consumption can be obtained and maintained by using the designed control system with the load distribution ratio as 0.2
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Tractive efficiency analysis for an intelligent air-Cushion tracked vehicle
2010Co-Authors: Mohiuddin A. K. M., Hossain Altab, Rahman, Mohammed Ataur, Aminanda YulfianAbstract:This study presents the tractive efficiency of an intelligent air-Cushion tracked vehicle (IACTV) working on swamp terrain. Based on the total power consumption and optimum load distribution for IACTV, two main issues are studied in this paper. First, a theoretical model is developed for optimizing total power consumption of the vehicle and tractive efficiency has been investigated with the effects of load distribution on the vehicle performance. Secondly, the vehicle has the ability to response for the changeable Cushion Pressure based on the Cushion height from the ground. The system is effective to control the intelligent air–Cushion system by measuring the vehicle tractive efficiency (TE), volume flow rate (Q), Cushion height (CH) and Cushion Pressure (CP). Experiment and simulation results showed that the optimal power consumption can be obtained and maintained by using the designed fuzzy logic system (FLS) with the load distribution ratio of 0.2 and tractive efficiency of 62%. The mean relative error of actual and predicted values from the FLS model on tractive efficiency is found as 9.2%, which is less than the acceptable limit of 10%. The goodness of fit of the prediction value from FLS is found as 0.96
Mohiuddin A. K. M. - One of the best experts on this subject based on the ideXlab platform.
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Intelligent air-Cushion tracked vehicle performance investigation: neural-networks
'Inderscience Publishers', 2012Co-Authors: Hossain Altab, Rahman, Mohammed Ataur, Mohiuddin A. K. M., Ramesh SinghAbstract:The Intelligent Air-Cushion Tracked Vehicle (IACTV) is given focus as an alternative to conventional off-road vehicles, which are driven by track and air-Cushion systems. To make the IACTV as effi cient as possible, proper investigation of the vehicle’s performance is essential. The most relevant factors that affect the competitive effi ciency of the (ACTV) are the Tractive Effort (TE), Motion Resistance (MR) and Power Consumption (PC). Therefore, an Artifi cial Neural-Network (ANN) model is proposed to investigate the vehicle’s performance. Cushion Clearance Height (CH), and Air-Cushion Pressure (CP)are used at the input layers, while PC, TE and MR are used at the output layers. Experiments are carried out in the fi eld to investigate the vehicle’s performance, and the fi ndings are compared with the results obtained from ANN
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Nonlinear controller of an air-Cushion system for a swamp terrain vehicle: fuzzy logic approach
Professional Engineering Publishing, 2011Co-Authors: Hossain Altab, Rahman, Mohammed Ataur, Mohiuddin A. K. M.Abstract:This paper presents the fuzzy logic controller (FLC) of an air-Cushion system for a swamp peat terrain vehicle and describes the process by which it functions. Cushion Pressure is controlled by an electronic proportional control valve and FLC using the output signal of the distance (height) measuring sensor that was attached to the vehicle. The main purpose of this study was to develop a control scheme for an air-Cushion system and to investigate the relationship between vehicle vertical position and the air-Cushion system, and to illustrate the important role of the fuzzy logic control system. Experimental values were recorded in the laboratory for control system testing, and in the swamp peat terrain field for vehicle performance investigation. In this paper, a fuzzy logic expert system (FLES) model, based on the Mamdani approach, was developed to predict the changes in flowrate. The mean relative error of actual and predicted values from the FLES model of lowrate was found to be slightly above the acceptable limit. The goodness of fit of the prediction values from the FLES model was found to be close to 1.0 as expected, and hence demonstrated the good performance of the developed system
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Development of an intelligent air-Cushion system for a swamp tracked vehicle
2010Co-Authors: Hossain Altab, Rahman, Mohammed Ataur, Mohiuddin A. K. M., Aminanda Yulfian, Muhidin ArifinAbstract:This paper describes the unique structure of an intelligent air –Cushion system for an intelligent air-Cushion track vehicle (IACTV) working on swamp terrain and its performance. Based on the total motion resistance and driving force analyzing for IACTV, the load distribution for the intelligent air-Cushion system and propulsion system are investigated respectively for minimizing the total power consumption. Two main issues are studied in this paper. First, a theoretical model is developed for optimizing total power consumption of the vehicle and the effects of load distribution on vehicle tractive effort and motion resistance. Secondly, the vehicle has the ability to response for the changeable Cushion Pressure based on the clearance height. The system is effective to control the intelligent air –Cushion system with measuring the vehicle tractive effort (TE), motion resistance (MR), power consumption (PC), Cushion clearance height (CH) and Cushion Pressure (CP). Ultrasonic displacement sensor, pull-in solenoid electromagnetic switch, Pressure control sensor, micro controller, and battery pH sensor are incorporated with the Fuzzy logic controller to investigate experimentally the TE, MR, PC, CH, and CP. Experiment and simulation results showed that the optimal power consumption can be obtained and maintained by using the designed control system with the load distribution ratio as 0.2
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Tractive efficiency analysis for an intelligent air-Cushion tracked vehicle
2010Co-Authors: Mohiuddin A. K. M., Hossain Altab, Rahman, Mohammed Ataur, Aminanda YulfianAbstract:This study presents the tractive efficiency of an intelligent air-Cushion tracked vehicle (IACTV) working on swamp terrain. Based on the total power consumption and optimum load distribution for IACTV, two main issues are studied in this paper. First, a theoretical model is developed for optimizing total power consumption of the vehicle and tractive efficiency has been investigated with the effects of load distribution on the vehicle performance. Secondly, the vehicle has the ability to response for the changeable Cushion Pressure based on the Cushion height from the ground. The system is effective to control the intelligent air–Cushion system by measuring the vehicle tractive efficiency (TE), volume flow rate (Q), Cushion height (CH) and Cushion Pressure (CP). Experiment and simulation results showed that the optimal power consumption can be obtained and maintained by using the designed fuzzy logic system (FLS) with the load distribution ratio of 0.2 and tractive efficiency of 62%. The mean relative error of actual and predicted values from the FLS model on tractive efficiency is found as 9.2%, which is less than the acceptable limit of 10%. The goodness of fit of the prediction value from FLS is found as 0.96
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Power consumption prediction for an intelligent air-Cushion tracked vehicle: fuzzy expert system
David Publishing USA, 2010Co-Authors: Hossain Altab, Rahman, Mohammed Ataur, Mohiuddin A. K. M., Aminanda YulfianAbstract:This paper describes the unique structure of an intelligent air-Cushion system of a hybrid electrical air-Cushion track vehicle working on swamp terrain. Fuzzy expert system (FES) is used in this study to control the swamp tracked vehicle’s intelligent air Cushion system while it operates in the swamp peat. The system will be effective to control the intelligent air-Cushion system with total power consumption (PC), Cushion clearance height (CCH) and Cushion Pressure (CP). Ultrasonic displacement sensor, pull-in solenoid electromagnetic switch, Pressure sensor, micro controller and battery pH sensor will be incorporated with the (FES) to investigate experimentally the PC, CCH and CP. In this study, we provide illustration how FES might play an important role in the prediction of power consumption of the vehicle’s intelligent air-Cushion system. The mean relative error of actual and predicted values from the FES model on total power consumption is found as 10.63 %, which is found to be alomst equal to the acceptable limits of 10%. The goodness of fit of the prediction values from the FES model on PC is found as 0.97
A. K. M. Mohiuddin - One of the best experts on this subject based on the ideXlab platform.
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Fuzzy Logic System for Tractive Performance Prediction of an Intelligent Air-Cushion Track Vehicle
2013Co-Authors: A. Hossain, A. Rahman, A. K. M. Mohiuddin, Yulfian AminAbstract:Abstract—Fuzzy logic system (FLS) is used in this study to predict the tractive performance in terms of traction force, and motion resistance for an intelligent air Cushion track vehicle while it operates in the swamp peat. The system is effective to control the intelligent air –Cushion system with measuring the vehicle traction force (TF), motion resistance (MR), Cushion clearance height (CH) and Cushion Pressure (CP). Ultrasonic displacement sensor, pull-in solenoid electromagnetic switch, Pressure control sensor, micro controller, and battery pH sensor are incorporated with the Fuzzy logic system to investigate experimentally the TF, MR, CH, and CP. In this study, a comparison for tractive performance of an intelligent air Cushion track vehicle has been performed with the results obtained from the predicted values of FLS and experimental actual values. The mean relative error of actual and predicted values from the FLS model on traction force, and total motion resistance are found as 5.58 %, and 6.78 % respectively. For all parameters, the relative error of predicted values are found to be less than the acceptable limits. The goodness of fit of the prediction values from the FLS model on TF, and MR are found as 0.90, and 0.98 respectively. Keywords—Cushion Pressure, Fuzzy logic, Motion resistance, Traction force
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Cushion Pressure control system for an intelligent air-Cushion track vehicle
Journal of Mechanical Science and Technology, 2011Co-Authors: A. Hossain, A. Rahman, A. K. M. MohiuddinAbstract:This paper presents the control system of Cushion Pressure for the developed intelligent air-Cushion track vehicle (IACTV) for operating on swamp terrain and wet fields. A novel auto-adjusting supporting system is designed for the vehicle’s intelligent air-Cushion system. Focusing on minimizing the total power demand of the vehicle, an optimization model has been established, for examining the effects of vehicle parameters and load distribution on power consumption by controlling air-Cushion Pressure. Then optimum Cushion Pressure is determined based on the developed optimum Pressure — sinkage relationship and the Pressure in the Cushion chamber is controlled by the Fuzzy controller by maintaining volume flow rate and continuously monitored by the Pressure sensor attached with the Cushion chamber. The ultrasonic displacement sensor is used to measure the sinkage of the vehicle. The output voltages of the ultrasonic displacement are used to operate the pull-in solenoid switch through the microcontroller which closes the circuit of the compressor motor. Distribution of vehicle load to the air-Cushion system is controlled by Fuzzy Logic controller by maintaining the inside Pressure of the Cushion.
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tractive performance prediction for intelligent air Cushion track vehicle fuzzy logic approach
World Academy of Science Engineering and Technology International Journal of Mechanical Aerospace Industrial Mechatronic and Manufacturing Engineering, 2010Co-Authors: A. Hossain, A. Rahman, A. K. M. Mohiuddin, Yulfian AminandaAbstract:Fuzzy logic approach is used in this study to predict the tractive performance in terms of traction force, and motion resistance for an intelligent air Cushion track vehicle while it operates in the swamp peat. The system is effective to control the intelligent air –Cushion system with measuring the vehicle traction force (TF), motion resistance (MR), Cushion clearance height (CH) and Cushion Pressure (CP). Sinkage measuring sensor, magnetic switch, Pressure sensor, micro controller, control valves and battery are incorporated with the Fuzzy logic system (FLS) to investigate experimentally the TF, MR, CH, and CP. In this study, a comparison for tractive performance of an intelligent air Cushion track vehicle has been performed with the results obtained from the predicted values of FLS and experimental actual values. The mean relative error of actual and predicted values from the FLS model on traction force, and total motion resistance are found as 5.58 %, and 6.78 % respectively. For all parameters, the relative error of predicted values are found to be less than the acceptable limits. The goodness of fit of the prediction values from the FLS model on TF, and MR are found as 0.90, and 0.98 respectively.
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intelligent air Cushion system of swamp peat vehicle control fuzzy logic technique
2009Co-Authors: A. Hossain, Mohammed Ataur Rahman, A. K. M. MohiuddinAbstract:This paper describes the fuzzy logic to control the intelligent air-Cushion system of swamp peat vehicle. Focusing on optimizing the total power consumption of the vehicle, two main issues were studied in this paper. First, a theoretical model is developed to minimize total power consumption of the vehicle. Second, a control scheme is proposed to achieve the control targets and to minimize the power consumption by using a fuzzy logic controller. Compared with traditional approach, fuzzy logic approach is more efficient for the representation, manipulation and utilization. Therefore, the primary purpose of this work was to investigate the relationship between total power consumption, clearance height and Cushion Pressure, and to illustrate how fuzzy logic technique might play an important role in prediction of total power consumption. All experimental values were collected from the field test using a developed prototype hybrid electrical air-Cushion tracked vehicle.
Rahman, Mohammed Ataur - One of the best experts on this subject based on the ideXlab platform.
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Intelligent air-Cushion tracked vehicle performance investigation: neural-networks
'Inderscience Publishers', 2012Co-Authors: Hossain Altab, Rahman, Mohammed Ataur, Mohiuddin A. K. M., Ramesh SinghAbstract:The Intelligent Air-Cushion Tracked Vehicle (IACTV) is given focus as an alternative to conventional off-road vehicles, which are driven by track and air-Cushion systems. To make the IACTV as effi cient as possible, proper investigation of the vehicle’s performance is essential. The most relevant factors that affect the competitive effi ciency of the (ACTV) are the Tractive Effort (TE), Motion Resistance (MR) and Power Consumption (PC). Therefore, an Artifi cial Neural-Network (ANN) model is proposed to investigate the vehicle’s performance. Cushion Clearance Height (CH), and Air-Cushion Pressure (CP)are used at the input layers, while PC, TE and MR are used at the output layers. Experiments are carried out in the fi eld to investigate the vehicle’s performance, and the fi ndings are compared with the results obtained from ANN
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Nonlinear controller of an air-Cushion system for a swamp terrain vehicle: fuzzy logic approach
Professional Engineering Publishing, 2011Co-Authors: Hossain Altab, Rahman, Mohammed Ataur, Mohiuddin A. K. M.Abstract:This paper presents the fuzzy logic controller (FLC) of an air-Cushion system for a swamp peat terrain vehicle and describes the process by which it functions. Cushion Pressure is controlled by an electronic proportional control valve and FLC using the output signal of the distance (height) measuring sensor that was attached to the vehicle. The main purpose of this study was to develop a control scheme for an air-Cushion system and to investigate the relationship between vehicle vertical position and the air-Cushion system, and to illustrate the important role of the fuzzy logic control system. Experimental values were recorded in the laboratory for control system testing, and in the swamp peat terrain field for vehicle performance investigation. In this paper, a fuzzy logic expert system (FLES) model, based on the Mamdani approach, was developed to predict the changes in flowrate. The mean relative error of actual and predicted values from the FLES model of lowrate was found to be slightly above the acceptable limit. The goodness of fit of the prediction values from the FLES model was found to be close to 1.0 as expected, and hence demonstrated the good performance of the developed system
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Intelligent air-Cushion tracked vehicle performance investigation: neural-networks
'Inderscience Publishers', 2011Co-Authors: Rahman, Mohammed Ataur, Hossain AltabAbstract:Intelligent air-Cushion tracked vehicle (IACTV) is focused for the alternatives to conventional off-road vehicles, which are driven by track system and air-Cushion system. To make IACTV as efficient as possible, proper investigation of vehicle performance is essential. However, most relevant factors that affect the competitive efficiency of the air-Cushion tracked vehicle are the tractive effort, motion resistance and power consumption. Therefore, an artificial neural-network (ANN) model is proposed to investigate the vehicle performance. Cushion clearance height (CH), and air-Cushion Pressure (CP) are used at the input layers while power consumption (PC), tractive effort (TE) and motion resistance (MR) are used at the output layers. Experiments are carried out in the field to investigate the vehicle performance and compared with the results obtained from ANN
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Development of an intelligent air-Cushion system for a swamp tracked vehicle
2010Co-Authors: Hossain Altab, Rahman, Mohammed Ataur, Mohiuddin A. K. M., Aminanda Yulfian, Muhidin ArifinAbstract:This paper describes the unique structure of an intelligent air –Cushion system for an intelligent air-Cushion track vehicle (IACTV) working on swamp terrain and its performance. Based on the total motion resistance and driving force analyzing for IACTV, the load distribution for the intelligent air-Cushion system and propulsion system are investigated respectively for minimizing the total power consumption. Two main issues are studied in this paper. First, a theoretical model is developed for optimizing total power consumption of the vehicle and the effects of load distribution on vehicle tractive effort and motion resistance. Secondly, the vehicle has the ability to response for the changeable Cushion Pressure based on the clearance height. The system is effective to control the intelligent air –Cushion system with measuring the vehicle tractive effort (TE), motion resistance (MR), power consumption (PC), Cushion clearance height (CH) and Cushion Pressure (CP). Ultrasonic displacement sensor, pull-in solenoid electromagnetic switch, Pressure control sensor, micro controller, and battery pH sensor are incorporated with the Fuzzy logic controller to investigate experimentally the TE, MR, PC, CH, and CP. Experiment and simulation results showed that the optimal power consumption can be obtained and maintained by using the designed control system with the load distribution ratio as 0.2
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Tractive efficiency analysis for an intelligent air-Cushion tracked vehicle
2010Co-Authors: Mohiuddin A. K. M., Hossain Altab, Rahman, Mohammed Ataur, Aminanda YulfianAbstract:This study presents the tractive efficiency of an intelligent air-Cushion tracked vehicle (IACTV) working on swamp terrain. Based on the total power consumption and optimum load distribution for IACTV, two main issues are studied in this paper. First, a theoretical model is developed for optimizing total power consumption of the vehicle and tractive efficiency has been investigated with the effects of load distribution on the vehicle performance. Secondly, the vehicle has the ability to response for the changeable Cushion Pressure based on the Cushion height from the ground. The system is effective to control the intelligent air–Cushion system by measuring the vehicle tractive efficiency (TE), volume flow rate (Q), Cushion height (CH) and Cushion Pressure (CP). Experiment and simulation results showed that the optimal power consumption can be obtained and maintained by using the designed fuzzy logic system (FLS) with the load distribution ratio of 0.2 and tractive efficiency of 62%. The mean relative error of actual and predicted values from the FLS model on tractive efficiency is found as 9.2%, which is less than the acceptable limit of 10%. The goodness of fit of the prediction value from FLS is found as 0.96
A. Hossain - One of the best experts on this subject based on the ideXlab platform.
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Fuzzy Logic System for Tractive Performance Prediction of an Intelligent Air-Cushion Track Vehicle
2013Co-Authors: A. Hossain, A. Rahman, A. K. M. Mohiuddin, Yulfian AminAbstract:Abstract—Fuzzy logic system (FLS) is used in this study to predict the tractive performance in terms of traction force, and motion resistance for an intelligent air Cushion track vehicle while it operates in the swamp peat. The system is effective to control the intelligent air –Cushion system with measuring the vehicle traction force (TF), motion resistance (MR), Cushion clearance height (CH) and Cushion Pressure (CP). Ultrasonic displacement sensor, pull-in solenoid electromagnetic switch, Pressure control sensor, micro controller, and battery pH sensor are incorporated with the Fuzzy logic system to investigate experimentally the TF, MR, CH, and CP. In this study, a comparison for tractive performance of an intelligent air Cushion track vehicle has been performed with the results obtained from the predicted values of FLS and experimental actual values. The mean relative error of actual and predicted values from the FLS model on traction force, and total motion resistance are found as 5.58 %, and 6.78 % respectively. For all parameters, the relative error of predicted values are found to be less than the acceptable limits. The goodness of fit of the prediction values from the FLS model on TF, and MR are found as 0.90, and 0.98 respectively. Keywords—Cushion Pressure, Fuzzy logic, Motion resistance, Traction force
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Cushion Pressure control system for an intelligent air-Cushion track vehicle
Journal of Mechanical Science and Technology, 2011Co-Authors: A. Hossain, A. Rahman, A. K. M. MohiuddinAbstract:This paper presents the control system of Cushion Pressure for the developed intelligent air-Cushion track vehicle (IACTV) for operating on swamp terrain and wet fields. A novel auto-adjusting supporting system is designed for the vehicle’s intelligent air-Cushion system. Focusing on minimizing the total power demand of the vehicle, an optimization model has been established, for examining the effects of vehicle parameters and load distribution on power consumption by controlling air-Cushion Pressure. Then optimum Cushion Pressure is determined based on the developed optimum Pressure — sinkage relationship and the Pressure in the Cushion chamber is controlled by the Fuzzy controller by maintaining volume flow rate and continuously monitored by the Pressure sensor attached with the Cushion chamber. The ultrasonic displacement sensor is used to measure the sinkage of the vehicle. The output voltages of the ultrasonic displacement are used to operate the pull-in solenoid switch through the microcontroller which closes the circuit of the compressor motor. Distribution of vehicle load to the air-Cushion system is controlled by Fuzzy Logic controller by maintaining the inside Pressure of the Cushion.
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tractive performance prediction for intelligent air Cushion track vehicle fuzzy logic approach
World Academy of Science Engineering and Technology International Journal of Mechanical Aerospace Industrial Mechatronic and Manufacturing Engineering, 2010Co-Authors: A. Hossain, A. Rahman, A. K. M. Mohiuddin, Yulfian AminandaAbstract:Fuzzy logic approach is used in this study to predict the tractive performance in terms of traction force, and motion resistance for an intelligent air Cushion track vehicle while it operates in the swamp peat. The system is effective to control the intelligent air –Cushion system with measuring the vehicle traction force (TF), motion resistance (MR), Cushion clearance height (CH) and Cushion Pressure (CP). Sinkage measuring sensor, magnetic switch, Pressure sensor, micro controller, control valves and battery are incorporated with the Fuzzy logic system (FLS) to investigate experimentally the TF, MR, CH, and CP. In this study, a comparison for tractive performance of an intelligent air Cushion track vehicle has been performed with the results obtained from the predicted values of FLS and experimental actual values. The mean relative error of actual and predicted values from the FLS model on traction force, and total motion resistance are found as 5.58 %, and 6.78 % respectively. For all parameters, the relative error of predicted values are found to be less than the acceptable limits. The goodness of fit of the prediction values from the FLS model on TF, and MR are found as 0.90, and 0.98 respectively.
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intelligent air Cushion system of swamp peat vehicle control fuzzy logic technique
2009Co-Authors: A. Hossain, Mohammed Ataur Rahman, A. K. M. MohiuddinAbstract:This paper describes the fuzzy logic to control the intelligent air-Cushion system of swamp peat vehicle. Focusing on optimizing the total power consumption of the vehicle, two main issues were studied in this paper. First, a theoretical model is developed to minimize total power consumption of the vehicle. Second, a control scheme is proposed to achieve the control targets and to minimize the power consumption by using a fuzzy logic controller. Compared with traditional approach, fuzzy logic approach is more efficient for the representation, manipulation and utilization. Therefore, the primary purpose of this work was to investigate the relationship between total power consumption, clearance height and Cushion Pressure, and to illustrate how fuzzy logic technique might play an important role in prediction of total power consumption. All experimental values were collected from the field test using a developed prototype hybrid electrical air-Cushion tracked vehicle.
