Pub Date : 2020-07-01DOI: 10.1109/ICEENG45378.2020.9171776
E. N. Mobarez, A. Sarhan, M. Ashry
This paper proposes a collaborative control system to be designed for multi-UAV. This makes it easy to perform many tasks at the same time and with high accuracy. Therefore, this cooperative control and guidance subsystems of the aircraft should have robust performance against sensors noise and wind disturbances. Four types of control algorithms were designed for a single Aerosonde UAV autopilot. This is to pick up which control algorithm is the best. As such, this control algorithm is proposed to be designed for the cooperative flight control system. Two classical control algorithms and two intelligent control algorithms have been proposed for the autopilot design of a single Aerosonde UAV. The first classical controller proposed is genetically tuned PID, while the second classical controller proposed is the fractional order PID. The first intelligent controller proposed for autopilot system is the Fuzzy logic controller known as FLC, while the second intelligent controller proposed is the adaptive neuro fuzzy inference system known as ANFIS. The proposed control algorithms have been applied to the nonlinear multivariable system of Aerosonde UAV. The analysis of simulation results assure that ANFIS is the best performance and the most robust control algorithm proposed. As such, ANFIS controller has been selected to be the cooperative flight controller system either in the low-level of a single UAV and in the top-level of multi-UAVs. Sometimes, classical controllers are preferred because of their simplicity in design. If this is the case, the simulation results assure that the genetically tuned fractional order PID controller- which proposed here for the first time with UAVs- is better than genetically tuned PID.
{"title":"Multi-variable Controllers for Cooperative Flight of Multi-Fixed Wing UAVs","authors":"E. N. Mobarez, A. Sarhan, M. Ashry","doi":"10.1109/ICEENG45378.2020.9171776","DOIUrl":"https://doi.org/10.1109/ICEENG45378.2020.9171776","url":null,"abstract":"This paper proposes a collaborative control system to be designed for multi-UAV. This makes it easy to perform many tasks at the same time and with high accuracy. Therefore, this cooperative control and guidance subsystems of the aircraft should have robust performance against sensors noise and wind disturbances. Four types of control algorithms were designed for a single Aerosonde UAV autopilot. This is to pick up which control algorithm is the best. As such, this control algorithm is proposed to be designed for the cooperative flight control system. Two classical control algorithms and two intelligent control algorithms have been proposed for the autopilot design of a single Aerosonde UAV. The first classical controller proposed is genetically tuned PID, while the second classical controller proposed is the fractional order PID. The first intelligent controller proposed for autopilot system is the Fuzzy logic controller known as FLC, while the second intelligent controller proposed is the adaptive neuro fuzzy inference system known as ANFIS. The proposed control algorithms have been applied to the nonlinear multivariable system of Aerosonde UAV. The analysis of simulation results assure that ANFIS is the best performance and the most robust control algorithm proposed. As such, ANFIS controller has been selected to be the cooperative flight controller system either in the low-level of a single UAV and in the top-level of multi-UAVs. Sometimes, classical controllers are preferred because of their simplicity in design. If this is the case, the simulation results assure that the genetically tuned fractional order PID controller- which proposed here for the first time with UAVs- is better than genetically tuned PID.","PeriodicalId":346636,"journal":{"name":"2020 12th International Conference on Electrical Engineering (ICEENG)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115522131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-01DOI: 10.1109/ICEENG45378.2020.9171734
Salem Abd El-Hakem Hegazy, AbdelMageed Mahmoud, A. Kamel, I. Arafa, Y. Elhalwagy
Inertial navigation system (INS) is utilized in several applications such as missile guidance, space navigation, and marine navigation. An efficient calibration method for improving the inertial navigation system accuracy is presented. As the vital error sources in the inertial navigation system are associated with the deterministic errors of the inertial measurement unit (IMU), the proposed technique precisely determines the calibration parameters to reduce these errors, especially the gyro’s scale factor, and non-orthogonality error. In recently proposed calibration methods, the scale factor is determined by the output/input relationship linear fitting. Although the determined scale factor meets the requirement of various navigation systems to some extent it doesn’t fit the high accurate ones, such as guided missiles and marines. That’s because the gyro damping effect is changed with different input angular rates which causes the gyro scale factor varying. The presented calibration method tackles this phenomenon by assigning different weights to each input rate through a weighted linear regression fit. Moreover, the gyro nonorthogonal error which comes from the imperfection gyro mounting is merely determined by the lateral coupling signal. But the fact is that the lateral coupling signal is not induced from the gyro non-orthogonal error only but also comprises the gyro signal which is directly proportional to the centripetal acceleration caused by the applied angular rates. Even though this signal is tiny but it will be accumulated for the long-time navigation system and degrades its accuracy. The presented calibration method utilizes a lateral accelerometer to realize that signal and tear out it to accurately obtain the nonorthogonal error. Finally, a laboratory test for the proposed method was carried out to ensure its effectiveness. Where the actual applied rates are determined twice, once with the built error model by the presented calibration method and the other by the traditional one.
{"title":"Calibration and Compensation of Scale Factor Non-linearity and Non-Orthogonality Errors for Dynamically Tuned Gyroscope (DTG)","authors":"Salem Abd El-Hakem Hegazy, AbdelMageed Mahmoud, A. Kamel, I. Arafa, Y. Elhalwagy","doi":"10.1109/ICEENG45378.2020.9171734","DOIUrl":"https://doi.org/10.1109/ICEENG45378.2020.9171734","url":null,"abstract":"Inertial navigation system (INS) is utilized in several applications such as missile guidance, space navigation, and marine navigation. An efficient calibration method for improving the inertial navigation system accuracy is presented. As the vital error sources in the inertial navigation system are associated with the deterministic errors of the inertial measurement unit (IMU), the proposed technique precisely determines the calibration parameters to reduce these errors, especially the gyro’s scale factor, and non-orthogonality error. In recently proposed calibration methods, the scale factor is determined by the output/input relationship linear fitting. Although the determined scale factor meets the requirement of various navigation systems to some extent it doesn’t fit the high accurate ones, such as guided missiles and marines. That’s because the gyro damping effect is changed with different input angular rates which causes the gyro scale factor varying. The presented calibration method tackles this phenomenon by assigning different weights to each input rate through a weighted linear regression fit. Moreover, the gyro nonorthogonal error which comes from the imperfection gyro mounting is merely determined by the lateral coupling signal. But the fact is that the lateral coupling signal is not induced from the gyro non-orthogonal error only but also comprises the gyro signal which is directly proportional to the centripetal acceleration caused by the applied angular rates. Even though this signal is tiny but it will be accumulated for the long-time navigation system and degrades its accuracy. The presented calibration method utilizes a lateral accelerometer to realize that signal and tear out it to accurately obtain the nonorthogonal error. Finally, a laboratory test for the proposed method was carried out to ensure its effectiveness. Where the actual applied rates are determined twice, once with the built error model by the presented calibration method and the other by the traditional one.","PeriodicalId":346636,"journal":{"name":"2020 12th International Conference on Electrical Engineering (ICEENG)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122239266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-01DOI: 10.1109/ICEENG45378.2020.9171711
M. Rabie, M. Aref, M. Hamdan, T. Gourlay
Colon cancer is the second and third of the highest risk cancers for both men and women, respectively. There is no definite approach to inhibit the disease, but there are some methods that can be followed for decreasing it. This includes certain types of diets, medicines like aspirin or pain killers and educating people about its accompanying symptoms. There are several methods for colorectal cancer screening for detection and investigation of this disease such as Physical exam, patient’s history, digital rectal exam, barium enema, sigmoidoscopy, virtual colonoscopy, colonoscopy and capsule-like devices are several methods for colorectal cancer screening to detect and investigate this disease.ANSYS FEA software have been utilized for designing and modelling the electromagnetic actuators. Different actuators have been investigated for the colonoscope guidance through difficult regions of the colon, with the objective of optimizing safe penetration and reducing the risk of perforation.The present work produced a framework for novel electromagnetic actuators that can be used for colonoscope actuation and navigation purposes, which can produce a uniformly distributed magnetic field capable of generating high magnetic forces.
{"title":"A New Approach for Colonosocpy Advanced Movement using Finite Element Analysis","authors":"M. Rabie, M. Aref, M. Hamdan, T. Gourlay","doi":"10.1109/ICEENG45378.2020.9171711","DOIUrl":"https://doi.org/10.1109/ICEENG45378.2020.9171711","url":null,"abstract":"Colon cancer is the second and third of the highest risk cancers for both men and women, respectively. There is no definite approach to inhibit the disease, but there are some methods that can be followed for decreasing it. This includes certain types of diets, medicines like aspirin or pain killers and educating people about its accompanying symptoms. There are several methods for colorectal cancer screening for detection and investigation of this disease such as Physical exam, patient’s history, digital rectal exam, barium enema, sigmoidoscopy, virtual colonoscopy, colonoscopy and capsule-like devices are several methods for colorectal cancer screening to detect and investigate this disease.ANSYS FEA software have been utilized for designing and modelling the electromagnetic actuators. Different actuators have been investigated for the colonoscope guidance through difficult regions of the colon, with the objective of optimizing safe penetration and reducing the risk of perforation.The present work produced a framework for novel electromagnetic actuators that can be used for colonoscope actuation and navigation purposes, which can produce a uniformly distributed magnetic field capable of generating high magnetic forces.","PeriodicalId":346636,"journal":{"name":"2020 12th International Conference on Electrical Engineering (ICEENG)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124684561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-01DOI: 10.1109/ICEENG45378.2020.9171717
A. H. Hassaballa, A. Kamel, I. Arafa, Y. Elhalwagy
Accurate measurements of angular velocities and linear accelerations are required to achieve a precise navigation solution for autonomous vehicles (AVs). These measurements are readily available from the inertial measurement unit (IMU) which is considered the most crucial component in the AV autopilot system. Inertial navigation system (INS) comprises of IMU plus complicated process that converts the IMU measurements to navigation information (position, velocity, attitude, and time (PVAT)). To use low grade IMUs for constructing a reliable INS, a precise mechanization model with an intensive aiding filter has to be implemented to integrate other sensors such as Global Positioning System (GPS) and magnetometers to insure trustable and continuous PVAT measurements. The motivation behind the work presented in this paper is to build a real time integrated navigation system using low-cost components available in the market. By using the proper calibration and error estimation techniques such as the extended Kalman filter (EKF), the system can achieve a comparable navigation accuracy with other higher performance navigation system. A linearized north-east-down (NED) error model is adopted, the GPS/INS integration using EKF is described. The algorithm is implemented on a low power ATSAM3X8E ARM Cortex-M3 series microcontrollers and integrated with an on the shelf MEMS 9-DOF IMU. The field experiments results analysis showed an outstanding real-time navigation performance if compared with high performance and much more expensive tactical grade INSs.
为了实现自动驾驶汽车(av)的精确导航解决方案，需要精确测量角速度和线性加速度。惯性测量单元(IMU)被认为是自动驾驶系统中最关键的部件，可以很容易地获得这些测量结果。惯性导航系统包括惯性单元和将惯性单元测量值转换为导航信息(位置、速度、姿态和时间)的复杂过程。为了使用低等级imu来构建可靠的INS，必须实现具有密集辅助滤波器的精确机械化模型，以集成其他传感器，如全球定位系统(GPS)和磁力计，以确保可靠和连续的PVAT测量。本文提出的工作背后的动机是使用市场上可用的低成本组件构建实时集成导航系统。通过适当的校正和误差估计技术，如扩展卡尔曼滤波(EKF)，该系统可以达到与其他高性能导航系统相当的导航精度。采用线性化的东北向下误差模型，描述了利用EKF进行GPS/INS集成的方法。该算法在低功耗ATSAM3X8E ARM Cortex-M3系列微控制器上实现，并与现成的MEMS 9自由度IMU集成。现场试验结果分析表明，与高性能、昂贵的战术级ins相比，该系统具有出色的实时导航性能。
{"title":"Real Time Full States Integrated Low Cost Navigation System for Autonomous Vehicles","authors":"A. H. Hassaballa, A. Kamel, I. Arafa, Y. Elhalwagy","doi":"10.1109/ICEENG45378.2020.9171717","DOIUrl":"https://doi.org/10.1109/ICEENG45378.2020.9171717","url":null,"abstract":"Accurate measurements of angular velocities and linear accelerations are required to achieve a precise navigation solution for autonomous vehicles (AVs). These measurements are readily available from the inertial measurement unit (IMU) which is considered the most crucial component in the AV autopilot system. Inertial navigation system (INS) comprises of IMU plus complicated process that converts the IMU measurements to navigation information (position, velocity, attitude, and time (PVAT)). To use low grade IMUs for constructing a reliable INS, a precise mechanization model with an intensive aiding filter has to be implemented to integrate other sensors such as Global Positioning System (GPS) and magnetometers to insure trustable and continuous PVAT measurements. The motivation behind the work presented in this paper is to build a real time integrated navigation system using low-cost components available in the market. By using the proper calibration and error estimation techniques such as the extended Kalman filter (EKF), the system can achieve a comparable navigation accuracy with other higher performance navigation system. A linearized north-east-down (NED) error model is adopted, the GPS/INS integration using EKF is described. The algorithm is implemented on a low power ATSAM3X8E ARM Cortex-M3 series microcontrollers and integrated with an on the shelf MEMS 9-DOF IMU. The field experiments results analysis showed an outstanding real-time navigation performance if compared with high performance and much more expensive tactical grade INSs.","PeriodicalId":346636,"journal":{"name":"2020 12th International Conference on Electrical Engineering (ICEENG)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130935479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-01DOI: 10.1109/ICEENG45378.2020.9171753
A. Youssef
Transportation relies heavily on fossil fuels. Rapid consumption of natural resources and emission of greenhouse gases due to burning of fossil fuels have prompted the automotive industry to develop sustainable and clean energy sources vehicles for urban transportation. Research and development have been carried out on vehicles driven by electricity generated through renewable sources as possible alternatives to conventional vehicles. Fuel cell electric vehicles (FCEVs) are among these vehicles, which provide a means for an efficient and environmentally friendly urban transportation system. High sensitivity to sudden changes in the loads and poor transient performance issue are the main obstacles for the commercialization of pure fuel cell driven vehicles; therefore, fuel cells are usually augmented with a secondary power source. Typical systems used in industrial vehicles use battery as a secondary power source. Using battery as a secondary power source for FCEVs provides additional peak power in situations such as accelerating and hill climbing, and recuperates braking energy by regeneration, thereby improves the performance and efficiency of the overall system. To manage the energy transfer between batteries and the DC-bus, a converter with bidirectional power flow capabilities is required; therefore, the objective of this paper is to design an appropriate bidirectional DC/DC converter structure or sometimes called an energy management converter to manage the charging and discharging of the battery based on high efficiency range. A multi-phase interleaved bidirectional DC/DC converter structure is proposed, which offers reduction of: input current ripples, stresses on switches, output voltage ripples, and passive component sizes. Improving transient response and reliability are among the many advantages of using such structure.
{"title":"Multiphase Interleaved Bidirectional DC/DC Converter for Fuel Cell/Battery Powered Electric Vehicles","authors":"A. Youssef","doi":"10.1109/ICEENG45378.2020.9171753","DOIUrl":"https://doi.org/10.1109/ICEENG45378.2020.9171753","url":null,"abstract":"Transportation relies heavily on fossil fuels. Rapid consumption of natural resources and emission of greenhouse gases due to burning of fossil fuels have prompted the automotive industry to develop sustainable and clean energy sources vehicles for urban transportation. Research and development have been carried out on vehicles driven by electricity generated through renewable sources as possible alternatives to conventional vehicles. Fuel cell electric vehicles (FCEVs) are among these vehicles, which provide a means for an efficient and environmentally friendly urban transportation system. High sensitivity to sudden changes in the loads and poor transient performance issue are the main obstacles for the commercialization of pure fuel cell driven vehicles; therefore, fuel cells are usually augmented with a secondary power source. Typical systems used in industrial vehicles use battery as a secondary power source. Using battery as a secondary power source for FCEVs provides additional peak power in situations such as accelerating and hill climbing, and recuperates braking energy by regeneration, thereby improves the performance and efficiency of the overall system. To manage the energy transfer between batteries and the DC-bus, a converter with bidirectional power flow capabilities is required; therefore, the objective of this paper is to design an appropriate bidirectional DC/DC converter structure or sometimes called an energy management converter to manage the charging and discharging of the battery based on high efficiency range. A multi-phase interleaved bidirectional DC/DC converter structure is proposed, which offers reduction of: input current ripples, stresses on switches, output voltage ripples, and passive component sizes. Improving transient response and reliability are among the many advantages of using such structure.","PeriodicalId":346636,"journal":{"name":"2020 12th International Conference on Electrical Engineering (ICEENG)","volume":"11 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133853758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-01DOI: 10.1109/ICEENG45378.2020.9171747
M. Ashry, Ahmed S. Mashaly, B. Sheta
Remote sensing is the backbone for several civilian and military applications. Synthetic Aperture Radar (SAR) is considered as one of the most important tools, which has a significant rule in remote sensing applications. For SAR signal processing, pulse compression techniques aim to obtain a fine map resolution, decrease the peak-transmitted power, and increase Signal to Noise Ratio (SNR) of the sensed target. In this paper, we introduce a performance assessment for two well-known Linear Frequency Modulation (LFM) pulse compression techniques, which are Matching Filtering and Stretch Processing. For matching filtering, it is known as Correlation processing technique. It is mainly used for narrow band and some medium band radar operations. While, stretch processing technique is usually used for high bandwidth LFM signal processing. Besides that, we discuss the properties of the LFM signal and the two compression techniques in both time and frequency domain. Also, the paper investigates the concept of the principle of stationary phase (POSP) and its use in deriving the frequency characteristics for the LFM signal and matched filter output. A mathematical model for each compression technique has been derived such that these models will be used for hardware implementation purpose. For simulation and performance assessment, the two techniques have been analyzed based on some quantitative indices like, Pulse Compression Ratio (PCR) and Peak Side-Lobe Ratio (PSLR).
{"title":"Comparative Analysis between SAR Pulse Compression Techniques","authors":"M. Ashry, Ahmed S. Mashaly, B. Sheta","doi":"10.1109/ICEENG45378.2020.9171747","DOIUrl":"https://doi.org/10.1109/ICEENG45378.2020.9171747","url":null,"abstract":"Remote sensing is the backbone for several civilian and military applications. Synthetic Aperture Radar (SAR) is considered as one of the most important tools, which has a significant rule in remote sensing applications. For SAR signal processing, pulse compression techniques aim to obtain a fine map resolution, decrease the peak-transmitted power, and increase Signal to Noise Ratio (SNR) of the sensed target. In this paper, we introduce a performance assessment for two well-known Linear Frequency Modulation (LFM) pulse compression techniques, which are Matching Filtering and Stretch Processing. For matching filtering, it is known as Correlation processing technique. It is mainly used for narrow band and some medium band radar operations. While, stretch processing technique is usually used for high bandwidth LFM signal processing. Besides that, we discuss the properties of the LFM signal and the two compression techniques in both time and frequency domain. Also, the paper investigates the concept of the principle of stationary phase (POSP) and its use in deriving the frequency characteristics for the LFM signal and matched filter output. A mathematical model for each compression technique has been derived such that these models will be used for hardware implementation purpose. For simulation and performance assessment, the two techniques have been analyzed based on some quantitative indices like, Pulse Compression Ratio (PCR) and Peak Side-Lobe Ratio (PSLR).","PeriodicalId":346636,"journal":{"name":"2020 12th International Conference on Electrical Engineering (ICEENG)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124279916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-01DOI: 10.1109/ICEENG45378.2020.9171715
Lionel Voirol, S. Guerrier, Yuming Zhang, Mucyo Karemera, Ahmed Radi
Different inertial sensor calibration techniques have been proposed to consider the sources of measurement error from inertial sensors. There has been a significant amount of literature which studies the stochastic errors calibration of such devices. The recent results of [1] have proved that among all possible methods the (Generalized Method of Wavelet Moments) (GMWM) presents various optimality and is computationally reliable. However, the GMWM estimators depend on weight matrix which considerably impact the quality of the estimated stochastic error models. In addition, such models are made of different components (typically high-frequency and low-frequency components) whose impacts on navigation vary depending on the context. For example, the high-frequency component of the error model may be more important when considering low-cost IMUs mounted on small size drones used for short-term missions. On the other hand, the situation may be reversed when considering navigational grade IMUs used, often autonomously, for long-term missions. With these differences, one may wish to select a GMWM estimator whose weight matrix has been tailored to estimate more reliably the elements of an error model believed to have the greatest impacts on navigation accuracy. In this article, we provide a formal answer to this question by proposing an optimally weighted GMWM estimator. Our results show that the proposed estimator is optimal for all parameters of the sensor error model we wish to estimate with the smallest possible uncertainty of the estimation. Therefore, regardless of the application, and independently of the context, the same optimally weighted estimator can be employed.
{"title":"Optimally Weighted Wavelet Variance-based Estimation for Inertial Sensor Stochastic Calibration","authors":"Lionel Voirol, S. Guerrier, Yuming Zhang, Mucyo Karemera, Ahmed Radi","doi":"10.1109/ICEENG45378.2020.9171715","DOIUrl":"https://doi.org/10.1109/ICEENG45378.2020.9171715","url":null,"abstract":"Different inertial sensor calibration techniques have been proposed to consider the sources of measurement error from inertial sensors. There has been a significant amount of literature which studies the stochastic errors calibration of such devices. The recent results of [1] have proved that among all possible methods the (Generalized Method of Wavelet Moments) (GMWM) presents various optimality and is computationally reliable. However, the GMWM estimators depend on weight matrix which considerably impact the quality of the estimated stochastic error models. In addition, such models are made of different components (typically high-frequency and low-frequency components) whose impacts on navigation vary depending on the context. For example, the high-frequency component of the error model may be more important when considering low-cost IMUs mounted on small size drones used for short-term missions. On the other hand, the situation may be reversed when considering navigational grade IMUs used, often autonomously, for long-term missions. With these differences, one may wish to select a GMWM estimator whose weight matrix has been tailored to estimate more reliably the elements of an error model believed to have the greatest impacts on navigation accuracy. In this article, we provide a formal answer to this question by proposing an optimally weighted GMWM estimator. Our results show that the proposed estimator is optimal for all parameters of the sensor error model we wish to estimate with the smallest possible uncertainty of the estimation. Therefore, regardless of the application, and independently of the context, the same optimally weighted estimator can be employed.","PeriodicalId":346636,"journal":{"name":"2020 12th International Conference on Electrical Engineering (ICEENG)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114257352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-01DOI: 10.1109/ICEENG45378.2020.9171740
H. Farghally, N. Ahmed, A. Nafeh, Emad A. Sweelem, F. Fahmy
This work design a domestic rainwater harvesting system located in Alexandria, Egypt. The considered rainwater harvesting system consists of; roof surface, conveyance system, storage tank and pump. A fuel cell system is used to feed the electrical load of the rainwater harvesting system. Neural Network Controller (NNC) is developed for achieving the desired fuel cell output power and energy management among the fuel cell and the load. A simulation model for the fuel cell has been developed using MATLAB/SMULINK. The evaluation of the controller is based on the time response characteristics of the system. The simulation results show that the system performance under different conditions has been verified using a load demand profile for both constant and step variation loads.
{"title":"Design and Control Strategy of PEM Fuel Cell for a Small Scale Rainwater Harvesting System","authors":"H. Farghally, N. Ahmed, A. Nafeh, Emad A. Sweelem, F. Fahmy","doi":"10.1109/ICEENG45378.2020.9171740","DOIUrl":"https://doi.org/10.1109/ICEENG45378.2020.9171740","url":null,"abstract":"This work design a domestic rainwater harvesting system located in Alexandria, Egypt. The considered rainwater harvesting system consists of; roof surface, conveyance system, storage tank and pump. A fuel cell system is used to feed the electrical load of the rainwater harvesting system. Neural Network Controller (NNC) is developed for achieving the desired fuel cell output power and energy management among the fuel cell and the load. A simulation model for the fuel cell has been developed using MATLAB/SMULINK. The evaluation of the controller is based on the time response characteristics of the system. The simulation results show that the system performance under different conditions has been verified using a load demand profile for both constant and step variation loads.","PeriodicalId":346636,"journal":{"name":"2020 12th International Conference on Electrical Engineering (ICEENG)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114132258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-01DOI: 10.1109/ICEENG45378.2020.9171701
Mohamed G Shehata, F. Ahmed, Sameh G. Salem, Hazem Zakaria
Frequency Modulated Continuous Wave (FMCW) radar has extensive areas of application for both civil and military use due to its good performance and detection capabilities. FMCW radar signal processing is based on two main modules; Moving Target Indicator (MTI) and Two-Dimensional Fast Fourier Transform (2D-FFT). Detection performance of FMCW radar is degraded due to the attenuation of the signals come from slowly moving targets with small visible Doppler frequencies. Also, the detection degradation of the targets whose beat frequency do not lie on the FFT grids. These problems have been introduced and overcome. In this paper, a complete design and implementation of LFMCW radar signal processor incorporating the solution of these problems are introduced on a field programmable gate array (FPGA) to facilitate real time processing. Simulation and experimental measurement are found to be identical illustrating the capability of the applied methods. The hardware implementation includes generation of the digital sawtooth waveform, Dechirping process,2D_FFT processing, Windowing, MTI, Single Delay Line Integrator and off pin filter.
{"title":"Design and Implementation of LFMCW Radar Signal Processor for Slowly Moving Target Detection Using FPGA","authors":"Mohamed G Shehata, F. Ahmed, Sameh G. Salem, Hazem Zakaria","doi":"10.1109/ICEENG45378.2020.9171701","DOIUrl":"https://doi.org/10.1109/ICEENG45378.2020.9171701","url":null,"abstract":"Frequency Modulated Continuous Wave (FMCW) radar has extensive areas of application for both civil and military use due to its good performance and detection capabilities. FMCW radar signal processing is based on two main modules; Moving Target Indicator (MTI) and Two-Dimensional Fast Fourier Transform (2D-FFT). Detection performance of FMCW radar is degraded due to the attenuation of the signals come from slowly moving targets with small visible Doppler frequencies. Also, the detection degradation of the targets whose beat frequency do not lie on the FFT grids. These problems have been introduced and overcome. In this paper, a complete design and implementation of LFMCW radar signal processor incorporating the solution of these problems are introduced on a field programmable gate array (FPGA) to facilitate real time processing. Simulation and experimental measurement are found to be identical illustrating the capability of the applied methods. The hardware implementation includes generation of the digital sawtooth waveform, Dechirping process,2D_FFT processing, Windowing, MTI, Single Delay Line Integrator and off pin filter.","PeriodicalId":346636,"journal":{"name":"2020 12th International Conference on Electrical Engineering (ICEENG)","volume":"21 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131057537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-01DOI: 10.1109/ICEENG45378.2020.9171723
Aya B. Elghonemy, A. El-Badawy
This paper focuses on the problem of robust H-infinity control design for a linear uncertain SISO system represented as a single-axis spacecraft rotation. The parametric uncertainty and disturbance input make this control problem a challenge. The paper presents an H-infinity control design which stabilizes all possible perturbed plants within the system and guarantees disturbance attenuation and meeting the tracking specifications while maintaining practical controller gains for all admissible uncertainties. The paper includes a design of a PD controller on the single-axis spacecraft plant and a comparison between the two controllers under the effect of disturbance and uncertainty. The robust H-infinity control problem is formulated into the General control problem formulation then solved via DK-iterations which is based on the concepts of H-infinityoptimization and μ-synthesis. The synthesized robust H-infinity controller is verified by nominal stability analysis, nominal performance analysis, robust stability analysis, robust performance analysis and worst case gain analysis, in addition to, testing the controller’s performance specifications.
{"title":"Robust H-infinity Controller for a Single-axis Spacecraft Rotation","authors":"Aya B. Elghonemy, A. El-Badawy","doi":"10.1109/ICEENG45378.2020.9171723","DOIUrl":"https://doi.org/10.1109/ICEENG45378.2020.9171723","url":null,"abstract":"This paper focuses on the problem of robust H-infinity control design for a linear uncertain SISO system represented as a single-axis spacecraft rotation. The parametric uncertainty and disturbance input make this control problem a challenge. The paper presents an H-infinity control design which stabilizes all possible perturbed plants within the system and guarantees disturbance attenuation and meeting the tracking specifications while maintaining practical controller gains for all admissible uncertainties. The paper includes a design of a PD controller on the single-axis spacecraft plant and a comparison between the two controllers under the effect of disturbance and uncertainty. The robust H-infinity control problem is formulated into the General control problem formulation then solved via DK-iterations which is based on the concepts of H-infinityoptimization and μ-synthesis. The synthesized robust H-infinity controller is verified by nominal stability analysis, nominal performance analysis, robust stability analysis, robust performance analysis and worst case gain analysis, in addition to, testing the controller’s performance specifications.","PeriodicalId":346636,"journal":{"name":"2020 12th International Conference on Electrical Engineering (ICEENG)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129613293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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