Pub Date : 2022-03-25DOI: 10.1109/ICCAE55086.2022.9762446
Yangfan Zhang, Jian Zhang
In this paper, an obstacle avoidance method for undersea unmanned vehicle (UUV) is proposed. The sensors employed are sonar-based ones, as the other type of sensors, like visual-based sensors, radar-based sensors are not viable for the underwater environments. The deformation of the obstacles has been observed and learnt with the combination of Back Propagation Neural Network (BPNN), and the coordinate position of the obstacle is predicted by the robot. The navigation algorithm applied could navigate the UUV avoiding collisions with the obstacles. The simulation results which could demonstrate the validation of our proposed algorithm are also presented, which are implemented by Matlab.
{"title":"An Obstacle Avoidance Method for Sonar-based Robots Avoiding Shape Changeable Obstacles*","authors":"Yangfan Zhang, Jian Zhang","doi":"10.1109/ICCAE55086.2022.9762446","DOIUrl":"https://doi.org/10.1109/ICCAE55086.2022.9762446","url":null,"abstract":"In this paper, an obstacle avoidance method for undersea unmanned vehicle (UUV) is proposed. The sensors employed are sonar-based ones, as the other type of sensors, like visual-based sensors, radar-based sensors are not viable for the underwater environments. The deformation of the obstacles has been observed and learnt with the combination of Back Propagation Neural Network (BPNN), and the coordinate position of the obstacle is predicted by the robot. The navigation algorithm applied could navigate the UUV avoiding collisions with the obstacles. The simulation results which could demonstrate the validation of our proposed algorithm are also presented, which are implemented by Matlab.","PeriodicalId":294641,"journal":{"name":"2022 14th International Conference on Computer and Automation Engineering (ICCAE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123844871","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 : 2022-03-25DOI: 10.1109/ICCAE55086.2022.9762420
Shraddha Mishra, Chi-Yi Tsai
In this paper, we present a novel quantum neural network (QNN) algorithm enhanced with transfer learning to perform multi-class image classification. The proposed QNN extracts quantum image encoding measurements through the quantum state tomography framework and passes the sampled features through the classical neural network architecture to the proposed learnable parameterized quantum circuit (PQC) followed by gradient update via quantum backpropagation. We benchmark three different PQCs to demonstrate that our proposed algorithm outperforms similar classical CNN architecture in test accuracy on CIFAR10 and MNIST datasets. Present results more prominently establish the success of PQC designs which will be further used in the design of 2D quantum convolutional neural network (QCNN).
{"title":"Design of Superior Parameterized Quantum Circuits for Quantum Image Classification","authors":"Shraddha Mishra, Chi-Yi Tsai","doi":"10.1109/ICCAE55086.2022.9762420","DOIUrl":"https://doi.org/10.1109/ICCAE55086.2022.9762420","url":null,"abstract":"In this paper, we present a novel quantum neural network (QNN) algorithm enhanced with transfer learning to perform multi-class image classification. The proposed QNN extracts quantum image encoding measurements through the quantum state tomography framework and passes the sampled features through the classical neural network architecture to the proposed learnable parameterized quantum circuit (PQC) followed by gradient update via quantum backpropagation. We benchmark three different PQCs to demonstrate that our proposed algorithm outperforms similar classical CNN architecture in test accuracy on CIFAR10 and MNIST datasets. Present results more prominently establish the success of PQC designs which will be further used in the design of 2D quantum convolutional neural network (QCNN).","PeriodicalId":294641,"journal":{"name":"2022 14th International Conference on Computer and Automation Engineering (ICCAE)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133943663","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 : 2022-03-25DOI: 10.1109/ICCAE55086.2022.9762428
Fang You, Jingyu Yao, Jianmin Wang
Because providing redundant information for in-vehicle human-computer interactions could increase work and cognitive load, this article developed a conceptual architecture for an in-vehicle adaptive human-computer interface (AHCI) to promote the implementation of a clearer and adaptable interface design, discussed the triggered factor based on context-awareness and multi-agent theories. The article presented how to create an appropriate methodology for developing in-vehicle AHCI that could address the demands of multiple users operating in dynamically changing task processing.
{"title":"Context-Triggered Factor of an In-vehicle Adaptive Human-Computer Interface Architecture Based on Context-Awareness and Multi-agent","authors":"Fang You, Jingyu Yao, Jianmin Wang","doi":"10.1109/ICCAE55086.2022.9762428","DOIUrl":"https://doi.org/10.1109/ICCAE55086.2022.9762428","url":null,"abstract":"Because providing redundant information for in-vehicle human-computer interactions could increase work and cognitive load, this article developed a conceptual architecture for an in-vehicle adaptive human-computer interface (AHCI) to promote the implementation of a clearer and adaptable interface design, discussed the triggered factor based on context-awareness and multi-agent theories. The article presented how to create an appropriate methodology for developing in-vehicle AHCI that could address the demands of multiple users operating in dynamically changing task processing.","PeriodicalId":294641,"journal":{"name":"2022 14th International Conference on Computer and Automation Engineering (ICCAE)","volume":"187 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131873574","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 : 2022-03-25DOI: 10.1109/ICCAE55086.2022.9762426
K. Kuzume, Ryo Nitta, Tomonari Masuzaki, Haruko Masuda, Hisashi Miyamaru
GPS-based navigation systems have been developed to support the walking of visually impaired people. However, their use in station premises and malls presented difficulties due to radio wave interference. In such places, an indoor navigation system (IDNS) was indispensable. Recently, an IDNS using geomagnetism that did not require the installation of new infrastructure attracted our attention. It incorporated technology to detect self-position by association with a geomagnetic fingerprint (GMFP) database, which included the geomagnetic vector of the current position, stored in advance on the cloud. However, to realize navigation over an entire floor, a detailed geomagnetic map of the floor was needed, taking a lot of time and labor to measure the geomagnetic field. In this research, we proposed a novel method that limited the area of the GMFP to places above braille blocks and linked the geometric maps to braille block maps. The main features of our system were as follows: (1) Reduction of labor and time required to make the GMFP; (2) Realization of a real-time navigation system with little error in estimated position; (3) A high-resolution geomagnetic map database could be easily made by walking with a nearly fixed stride length without any specific equipment. To confirm the principal operation of our system, we made a prototype system. We then evaluated the performance of our system under various experimental conditions. Finally, we demonstrated a simple navigation system. As a result, we were able to confirm that our system could estimate self-position in real-time with little error and provide simple navigation for visually impaired people.
{"title":"Development of Walking Assistance System for Visually Impaired People Using Geomagnetic Fingerprint and Braille Block Map","authors":"K. Kuzume, Ryo Nitta, Tomonari Masuzaki, Haruko Masuda, Hisashi Miyamaru","doi":"10.1109/ICCAE55086.2022.9762426","DOIUrl":"https://doi.org/10.1109/ICCAE55086.2022.9762426","url":null,"abstract":"GPS-based navigation systems have been developed to support the walking of visually impaired people. However, their use in station premises and malls presented difficulties due to radio wave interference. In such places, an indoor navigation system (IDNS) was indispensable. Recently, an IDNS using geomagnetism that did not require the installation of new infrastructure attracted our attention. It incorporated technology to detect self-position by association with a geomagnetic fingerprint (GMFP) database, which included the geomagnetic vector of the current position, stored in advance on the cloud. However, to realize navigation over an entire floor, a detailed geomagnetic map of the floor was needed, taking a lot of time and labor to measure the geomagnetic field. In this research, we proposed a novel method that limited the area of the GMFP to places above braille blocks and linked the geometric maps to braille block maps. The main features of our system were as follows: (1) Reduction of labor and time required to make the GMFP; (2) Realization of a real-time navigation system with little error in estimated position; (3) A high-resolution geomagnetic map database could be easily made by walking with a nearly fixed stride length without any specific equipment. To confirm the principal operation of our system, we made a prototype system. We then evaluated the performance of our system under various experimental conditions. Finally, we demonstrated a simple navigation system. As a result, we were able to confirm that our system could estimate self-position in real-time with little error and provide simple navigation for visually impaired people.","PeriodicalId":294641,"journal":{"name":"2022 14th International Conference on Computer and Automation Engineering (ICCAE)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123318438","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 : 2022-03-25DOI: 10.1109/ICCAE55086.2022.9762424
K. Hou, Yingzi Tan
This paper establishes a kinematics model for a wall-climbing robot with rear-wheel steering, conducts kinematics analysis, and derives the corresponding formula. Through analysis, it is concluded that the robot's motion trajectory is a combination of a circular arc and a straight line. For the adjustment of different distances and poses, a variety of path planning methods such as arc circumscribed, arc combined with straight lines, and arc inscribed are designed, and the parameter values that need to be determined in each planning method are deduced. In this paper, Matlab software is used for simulation, the expected pose transformation is realized, and the feasibility of the theory is verified. Finally, several path planning methods are compared to determine their respective applicable conditions.
{"title":"Kinematics Analysis and Path Planning of Wall-Climbing Robot Based on Rear-Wheel Steering","authors":"K. Hou, Yingzi Tan","doi":"10.1109/ICCAE55086.2022.9762424","DOIUrl":"https://doi.org/10.1109/ICCAE55086.2022.9762424","url":null,"abstract":"This paper establishes a kinematics model for a wall-climbing robot with rear-wheel steering, conducts kinematics analysis, and derives the corresponding formula. Through analysis, it is concluded that the robot's motion trajectory is a combination of a circular arc and a straight line. For the adjustment of different distances and poses, a variety of path planning methods such as arc circumscribed, arc combined with straight lines, and arc inscribed are designed, and the parameter values that need to be determined in each planning method are deduced. In this paper, Matlab software is used for simulation, the expected pose transformation is realized, and the feasibility of the theory is verified. Finally, several path planning methods are compared to determine their respective applicable conditions.","PeriodicalId":294641,"journal":{"name":"2022 14th International Conference on Computer and Automation Engineering (ICCAE)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129991158","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 : 2022-03-25DOI: 10.1109/ICCAE55086.2022.9762436
Diana Rose A. Tambogon, A. Yumang
Garlic is one of the main crops the Philippines produce every year. Currently, this is cultivated in the traditional way wherein farmers used soil as its growing medium. A hydroponic system is a new method of planting that has a promising output in a better quality of production. This study focused on the cultivation of garlic as the testing plant in the Ebb and Flow hydroponic system and in the traditional way. An IoT-based monitoring system is also implemented in the study to monitor the pH, Electrical Conductivity (EC), and water temperature of the hydroponic system. The monitoring system used ThingSpeak to store, analyze, and visualize the acquired data by the sensors. As well as the IoT ThingSpeak Monitor Widget to monitor the data in the user’s mobile phone widget. The data that were gathered for the statistical treatment for both the traditional and the hydroponic system are the height of the plant’s leaves for the 20 days after transplant (DAT), 40 DAT, 60 DAT, bulb diameter at 60 DAT, and fresh weight at 60 DAT. Based on the statistical result, it was concluded that the Ebb and Flow hydroponic system has better plant production compared to that of the traditional.
{"title":"Growth of Garlic in Hydroponic System with IoT-Based Monitoring","authors":"Diana Rose A. Tambogon, A. Yumang","doi":"10.1109/ICCAE55086.2022.9762436","DOIUrl":"https://doi.org/10.1109/ICCAE55086.2022.9762436","url":null,"abstract":"Garlic is one of the main crops the Philippines produce every year. Currently, this is cultivated in the traditional way wherein farmers used soil as its growing medium. A hydroponic system is a new method of planting that has a promising output in a better quality of production. This study focused on the cultivation of garlic as the testing plant in the Ebb and Flow hydroponic system and in the traditional way. An IoT-based monitoring system is also implemented in the study to monitor the pH, Electrical Conductivity (EC), and water temperature of the hydroponic system. The monitoring system used ThingSpeak to store, analyze, and visualize the acquired data by the sensors. As well as the IoT ThingSpeak Monitor Widget to monitor the data in the user’s mobile phone widget. The data that were gathered for the statistical treatment for both the traditional and the hydroponic system are the height of the plant’s leaves for the 20 days after transplant (DAT), 40 DAT, 60 DAT, bulb diameter at 60 DAT, and fresh weight at 60 DAT. Based on the statistical result, it was concluded that the Ebb and Flow hydroponic system has better plant production compared to that of the traditional.","PeriodicalId":294641,"journal":{"name":"2022 14th International Conference on Computer and Automation Engineering (ICCAE)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122831096","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 : 2022-03-25DOI: 10.1109/ICCAE55086.2022.9762425
Clarisse Anne Borja, Kyle Joshua Tisado, C. Ostia
Diagnosis of motor faults plays an important role in the industry to implement preventive maintenance and avoid an unscheduled shutdown. A mechanical fault diagnostic system of a BLDC using the k-NN classification technique with DWT feature extraction is proposed in this study. Voltage signals from healthy and faulty BLDC motors were recorded. The voltage signals of the motors were then decomposed, and features were extracted using the DWT and divided into three data sets which are: training, validation, and testing. The k-NN prediction model was then trained, validated, and tested using a MATLAB environment. The diagnosis was run on 5 different Haar levels. Results showed that Level 1 produced the highest accuracy of 89.510% over the other 4 levels and was statistically verified using ANOVA Test.
{"title":"Fault Diagnosis of a Brushless DC Motor Using K-Nearest Neighbor Classification Technique with Discrete Wavelet Transform Feature Extraction","authors":"Clarisse Anne Borja, Kyle Joshua Tisado, C. Ostia","doi":"10.1109/ICCAE55086.2022.9762425","DOIUrl":"https://doi.org/10.1109/ICCAE55086.2022.9762425","url":null,"abstract":"Diagnosis of motor faults plays an important role in the industry to implement preventive maintenance and avoid an unscheduled shutdown. A mechanical fault diagnostic system of a BLDC using the k-NN classification technique with DWT feature extraction is proposed in this study. Voltage signals from healthy and faulty BLDC motors were recorded. The voltage signals of the motors were then decomposed, and features were extracted using the DWT and divided into three data sets which are: training, validation, and testing. The k-NN prediction model was then trained, validated, and tested using a MATLAB environment. The diagnosis was run on 5 different Haar levels. Results showed that Level 1 produced the highest accuracy of 89.510% over the other 4 levels and was statistically verified using ANOVA Test.","PeriodicalId":294641,"journal":{"name":"2022 14th International Conference on Computer and Automation Engineering (ICCAE)","volume":"14 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120883777","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 : 2022-03-25DOI: 10.1109/ICCAE55086.2022.9762417
Tohmy Brain P. Espinosa, G. Magwili
Rapid growth of power electronic and smart technology used in the industry is one of the key challenges in energy sector. The most common cause of power quality issues in power system is the harmonics which generated by nonlinear loads. Harmonics produce power quality issues and harmful effect on the electrical distribution network. Thus, to improve the power system quality and reliability, it is important to suppress the harmonic distortion cause by nonlinear loads. Traditional passive filters are commonly utilized in the industry but due to its limitation in compensation and production of resonance condition, active power filters are considered the most feasible solution. This study introduces a new design control strategy for Shunt Active power filter (SAPF) using synchronous reference frame (SRF) method for reference current generation, phase locked loop (PLL) and hysteresis current controller to mitigate the harmonic in a three phase distribution system. The design was modelled and simulated using MATLAB/Simulink. The study used IEEE Standard 519-2014 in compliance with the recommended limits of harmonics distortion. A three phase electrical distribution system was modelled and simulated for both balance and unbalance load condition to determine the harmonic distortion caused by nonlinear loads. The proposed SAPF was then connected parallel to the main distribution network to mitigate the harmonics presence in the system. The simulation results validates that the SAPF using SRF with PLL and hysteresis current controller was capable to extract the harmonic currents and generate a compensating current that will be injected back to the line to mitigate the harmonic distortion for both balance and unbalance load condition. Moreover, the results demonstrate that the individual harmonic current distortion are kept within the limit and acceptable harmonic values recommended as per IEEE standard.
{"title":"Synchronous Reference Frame Method with PLL and Hysteresis Current Controller for Three Phase Shunt Active Power Filter to Mitigate Harmonics Caused by Nonlinear Loads","authors":"Tohmy Brain P. Espinosa, G. Magwili","doi":"10.1109/ICCAE55086.2022.9762417","DOIUrl":"https://doi.org/10.1109/ICCAE55086.2022.9762417","url":null,"abstract":"Rapid growth of power electronic and smart technology used in the industry is one of the key challenges in energy sector. The most common cause of power quality issues in power system is the harmonics which generated by nonlinear loads. Harmonics produce power quality issues and harmful effect on the electrical distribution network. Thus, to improve the power system quality and reliability, it is important to suppress the harmonic distortion cause by nonlinear loads. Traditional passive filters are commonly utilized in the industry but due to its limitation in compensation and production of resonance condition, active power filters are considered the most feasible solution. This study introduces a new design control strategy for Shunt Active power filter (SAPF) using synchronous reference frame (SRF) method for reference current generation, phase locked loop (PLL) and hysteresis current controller to mitigate the harmonic in a three phase distribution system. The design was modelled and simulated using MATLAB/Simulink. The study used IEEE Standard 519-2014 in compliance with the recommended limits of harmonics distortion. A three phase electrical distribution system was modelled and simulated for both balance and unbalance load condition to determine the harmonic distortion caused by nonlinear loads. The proposed SAPF was then connected parallel to the main distribution network to mitigate the harmonics presence in the system. The simulation results validates that the SAPF using SRF with PLL and hysteresis current controller was capable to extract the harmonic currents and generate a compensating current that will be injected back to the line to mitigate the harmonic distortion for both balance and unbalance load condition. Moreover, the results demonstrate that the individual harmonic current distortion are kept within the limit and acceptable harmonic values recommended as per IEEE standard.","PeriodicalId":294641,"journal":{"name":"2022 14th International Conference on Computer and Automation Engineering (ICCAE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125351530","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 : 2022-03-25DOI: 10.1109/ICCAE55086.2022.9762418
Manuel Micko D. Quintana, Ronald Renz D. Infante, Jinel Cireel S. Torrano, M. Pacis
Avian diseases have been the prevalent cause of shortage in poultry demand. While preventive and control measures can be applied to address this concern, disease identification and verification has been a challenge – especially considering the fact that the modern solutions are costly and are not compatible for remote usage. With this, the researchers proposed the development of a hybrid solar-powered chicken disease monitoring system using decision tree models as the learning algorithm for identification using visual and acoustic inputs from the chickens. The learning algorithm identifies six different symptoms from chickens (slouching, eye foaming, lethargy, feather loss, color paling, and raling) from 15 different chicken samples. Throughout the experimentation of continuous monitoring for 72 hours, the learning model was calculated to have 84.6% accuracy in classifying diseased chickens when only visual imagery is considered, and 86.1% accuracy when audio inputs are also provided. With the integration of the hybrid solar-power system, the system can still continuously operate for 8 hour of power downtime.
{"title":"A Hybrid Solar Powered Chicken Disease Monitoring System using Decision Tree Models with Visual and Acoustic Imagery","authors":"Manuel Micko D. Quintana, Ronald Renz D. Infante, Jinel Cireel S. Torrano, M. Pacis","doi":"10.1109/ICCAE55086.2022.9762418","DOIUrl":"https://doi.org/10.1109/ICCAE55086.2022.9762418","url":null,"abstract":"Avian diseases have been the prevalent cause of shortage in poultry demand. While preventive and control measures can be applied to address this concern, disease identification and verification has been a challenge – especially considering the fact that the modern solutions are costly and are not compatible for remote usage. With this, the researchers proposed the development of a hybrid solar-powered chicken disease monitoring system using decision tree models as the learning algorithm for identification using visual and acoustic inputs from the chickens. The learning algorithm identifies six different symptoms from chickens (slouching, eye foaming, lethargy, feather loss, color paling, and raling) from 15 different chicken samples. Throughout the experimentation of continuous monitoring for 72 hours, the learning model was calculated to have 84.6% accuracy in classifying diseased chickens when only visual imagery is considered, and 86.1% accuracy when audio inputs are also provided. With the integration of the hybrid solar-power system, the system can still continuously operate for 8 hour of power downtime.","PeriodicalId":294641,"journal":{"name":"2022 14th International Conference on Computer and Automation Engineering (ICCAE)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116917838","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 : 2022-03-25DOI: 10.1109/ICCAE55086.2022.9762448
E. S. Ghith, F. A. Tolba
This paper presents a new approach to control the position of the micro-robotics system with a proportional-integral-derivative (PID) controller. By using Whale Optimization Algorithm (WOA), the optimal PID controller indicators were obtained by applying a new objective function namely, integral square time multiplied square error (ISTES). The efficiency of the proposed WOA-based controller was verified by comparisons made with Grey Wolf Optimization (GWO) algorithm-based controllers in terms of time. Each control technique will be applied to the identified model using MATLAB Simulink and the experimental test facility was conducted using LABVIEW software. The simulation and experimental results show that the performance of WOA-PID controller based on ISTES cost function achieves the best performance among various techniques. Moreover, the WOA technique had the highest performance compared to GWO technique based on rising time, setting time and settling error. Thus, it is recommended to apply WOA for tuning the parameters of PID as it can enhance its performance in micro-robotic systems. It was found that the amount of error is reduced by 47.5% using WOA than other former experiments.
{"title":"Real-Time Implementation of Tuning PID Controller Based on Whale Optimization Algorithm for Micro-robotics System","authors":"E. S. Ghith, F. A. Tolba","doi":"10.1109/ICCAE55086.2022.9762448","DOIUrl":"https://doi.org/10.1109/ICCAE55086.2022.9762448","url":null,"abstract":"This paper presents a new approach to control the position of the micro-robotics system with a proportional-integral-derivative (PID) controller. By using Whale Optimization Algorithm (WOA), the optimal PID controller indicators were obtained by applying a new objective function namely, integral square time multiplied square error (ISTES). The efficiency of the proposed WOA-based controller was verified by comparisons made with Grey Wolf Optimization (GWO) algorithm-based controllers in terms of time. Each control technique will be applied to the identified model using MATLAB Simulink and the experimental test facility was conducted using LABVIEW software. The simulation and experimental results show that the performance of WOA-PID controller based on ISTES cost function achieves the best performance among various techniques. Moreover, the WOA technique had the highest performance compared to GWO technique based on rising time, setting time and settling error. Thus, it is recommended to apply WOA for tuning the parameters of PID as it can enhance its performance in micro-robotic systems. It was found that the amount of error is reduced by 47.5% using WOA than other former experiments.","PeriodicalId":294641,"journal":{"name":"2022 14th International Conference on Computer and Automation Engineering (ICCAE)","volume":"306 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131934680","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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