Pub Date : 2020-01-31DOI: 10.15866/ireaco.v13i1.18130
C. K. Wachjoe, Hermagasantos Zein, J. Raharjo
Optimal scheduling of the generating units in one hour ahead considerably affects the electricity cost because the fuel cost component will bring up the economic load dispatch problem. Fuel cost is an essential parameter to calculate the optimal cost function of the power systems subject to the operating constraints and transmission loss. Generally, the economic load dispatch problem is resolved through the iteration step and using many variables so that it uses long computation time. The accuracy can also be low because the point of the solution can fall near the minimum local point. This paper proposes a method to provide better efficiency and accuracy of the economic load dispatch problem. The methodology forms a fuel cost function in the quadratic equation mathematically derived in order to obtain a faster solution without iteration processes. The B-loss matrix determines the transmission loss after receiving the optimal solution without considering transmission losses. The method validation simulates the economic load dispatch for the 26-Bus power system and the 6-generating units. After comparing with the Genetic Algorithm, the proposed method can save fuel costs significantly of about $ 29876.46 in 24 hours, while computing time in executing the application program is short enough, namely 0.15 seconds.
{"title":"A Fast Scheduling Method to Solve Economic Load Dispatch Problem","authors":"C. K. Wachjoe, Hermagasantos Zein, J. Raharjo","doi":"10.15866/ireaco.v13i1.18130","DOIUrl":"https://doi.org/10.15866/ireaco.v13i1.18130","url":null,"abstract":"Optimal scheduling of the generating units in one hour ahead considerably affects the electricity cost because the fuel cost component will bring up the economic load dispatch problem. Fuel cost is an essential parameter to calculate the optimal cost function of the power systems subject to the operating constraints and transmission loss. Generally, the economic load dispatch problem is resolved through the iteration step and using many variables so that it uses long computation time. The accuracy can also be low because the point of the solution can fall near the minimum local point. This paper proposes a method to provide better efficiency and accuracy of the economic load dispatch problem. The methodology forms a fuel cost function in the quadratic equation mathematically derived in order to obtain a faster solution without iteration processes. The B-loss matrix determines the transmission loss after receiving the optimal solution without considering transmission losses. The method validation simulates the economic load dispatch for the 26-Bus power system and the 6-generating units. After comparing with the Genetic Algorithm, the proposed method can save fuel costs significantly of about $ 29876.46 in 24 hours, while computing time in executing the application program is short enough, namely 0.15 seconds.","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"13 1","pages":"12-18"},"PeriodicalIF":0.0,"publicationDate":"2020-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47400512","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 : 2020-01-31DOI: 10.15866/ireaco.v13i1.18213
Gulnur Tolebi, N. S. Dairbekov, D. Kurmankhojayev
{"title":"Link Flow Estimation on an Isolated Intersection Based on Deep Learning Models","authors":"Gulnur Tolebi, N. S. Dairbekov, D. Kurmankhojayev","doi":"10.15866/ireaco.v13i1.18213","DOIUrl":"https://doi.org/10.15866/ireaco.v13i1.18213","url":null,"abstract":"","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"13 1","pages":"19"},"PeriodicalIF":0.0,"publicationDate":"2020-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43204824","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 : 2020-01-31DOI: 10.15866/ireaco.v13i1.18504
Setiawardhana Setiawardhana, Rudy Dikairono, D. Purwanto, T. A. Sardjono
{"title":"Ball Position Estimation in Goal Keeper Robots Using Neural Network","authors":"Setiawardhana Setiawardhana, Rudy Dikairono, D. Purwanto, T. A. Sardjono","doi":"10.15866/ireaco.v13i1.18504","DOIUrl":"https://doi.org/10.15866/ireaco.v13i1.18504","url":null,"abstract":"","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"13 1","pages":"38"},"PeriodicalIF":0.0,"publicationDate":"2020-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42996863","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 : 2019-11-30DOI: 10.15866/ireaco.v12i6.17395
O. Qudsi, S. Sutedjo, E. Purwanto, D. S. Yanaratri, Laily Fajarwati
This paper shows detailed design and implementation of SPWM inverters for single-phase induction motor speed control. The technique proposed in this paper is a constant V/f one. A constant V/f technique is used to set fluxes on the air gap; it can be kept constant by keeping the ratio between voltage and frequency constant. Therefore, a single-phase induction motor will maintain the ability of torque at each speed. With a constant V/f technique, an induction motor can operate at relatively constant torque. In this paper, the FLC is used as a speed controller. FLC has good performance with the fast response time. The design results have been implemented using a single-phase induction motor while maintaining a speed of 1200 rpm. Based on the test results, in order to reach the setpoint, the response time value is 0.061 seconds. When given interference, FLC performance can work to restore speed according to the setpoint.
{"title":"Real Single-Phase V/f SPWM Inverter for Induction Motor Speed Control Using Fuzzy Logic Controller","authors":"O. Qudsi, S. Sutedjo, E. Purwanto, D. S. Yanaratri, Laily Fajarwati","doi":"10.15866/ireaco.v12i6.17395","DOIUrl":"https://doi.org/10.15866/ireaco.v12i6.17395","url":null,"abstract":"This paper shows detailed design and implementation of SPWM inverters for single-phase induction motor speed control. The technique proposed in this paper is a constant V/f one. A constant V/f technique is used to set fluxes on the air gap; it can be kept constant by keeping the ratio between voltage and frequency constant. Therefore, a single-phase induction motor will maintain the ability of torque at each speed. With a constant V/f technique, an induction motor can operate at relatively constant torque. In this paper, the FLC is used as a speed controller. FLC has good performance with the fast response time. The design results have been implemented using a single-phase induction motor while maintaining a speed of 1200 rpm. Based on the test results, in order to reach the setpoint, the response time value is 0.061 seconds. When given interference, FLC performance can work to restore speed according to the setpoint.","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"12 1","pages":"262-270"},"PeriodicalIF":0.0,"publicationDate":"2019-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43882977","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 : 2019-11-30DOI: 10.15866/ireaco.v12i6.17456
D. Puangdownreong
{"title":"A Novel Fractional-Order PIλDμAν Controller and Its Design Optimization Based on Spiritual Search","authors":"D. Puangdownreong","doi":"10.15866/ireaco.v12i6.17456","DOIUrl":"https://doi.org/10.15866/ireaco.v12i6.17456","url":null,"abstract":"","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"12 1","pages":"271"},"PeriodicalIF":0.0,"publicationDate":"2019-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41704381","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 : 2019-11-30DOI: 10.15866/ireaco.v12i6.18388
G. Valencia, Jorge Duarte, L. Obregon
The main source of renewable energy available in nature is solar radiation, which is the most promising resource to replace non-renewable energy sources and reduce gas emissions into the atmosphere since it allows various forms of capture and transformation through photovoltaic and photothermal systems. For an optimum use of solar energy, it is necessary to characterize and know the solar radiation at the level of the earth's surface, but this varies with time instantaneously, hourly, daily, and during seasons, with the latitude and with the local microclimates of the site. Therefore, a backpropagation artificial neural network (ANN) has been used to develop a mathematical model to predict solar radiation and the polycrystalline temperature, as a function of the ambient in the Colombian territory, specifically in the Atlantic coast. The network has been trained with 300 of the 381 data that constituted the matrix to obtain the RMSE that has been 0.164, with a network architecture composed of 10 layers and 5 neurons per layer. In addition, it has been used as a learning constant of 0.5 for each interconnection of the ANN. The increase in the number of hidden layers and the number of neurons increases the network performance, improving the prediction of the objective variable around 13% when using an architecture with five neurons per layer (NL), and 15 numbers of layers (L). In general, the results obtained have shown an acceptable performance of the artificial neural network in the estimation of solar radiation, but with certain possibilities of being improved.
{"title":"Global Solar Radiation Prediction in Colombia Using a Backpropagation Neural Network Architecture","authors":"G. Valencia, Jorge Duarte, L. Obregon","doi":"10.15866/ireaco.v12i6.18388","DOIUrl":"https://doi.org/10.15866/ireaco.v12i6.18388","url":null,"abstract":"The main source of renewable energy available in nature is solar radiation, which is the most promising resource to replace non-renewable energy sources and reduce gas emissions into the atmosphere since it allows various forms of capture and transformation through photovoltaic and photothermal systems. For an optimum use of solar energy, it is necessary to characterize and know the solar radiation at the level of the earth's surface, but this varies with time instantaneously, hourly, daily, and during seasons, with the latitude and with the local microclimates of the site. Therefore, a backpropagation artificial neural network (ANN) has been used to develop a mathematical model to predict solar radiation and the polycrystalline temperature, as a function of the ambient in the Colombian territory, specifically in the Atlantic coast. The network has been trained with 300 of the 381 data that constituted the matrix to obtain the RMSE that has been 0.164, with a network architecture composed of 10 layers and 5 neurons per layer. In addition, it has been used as a learning constant of 0.5 for each interconnection of the ANN. The increase in the number of hidden layers and the number of neurons increases the network performance, improving the prediction of the objective variable around 13% when using an architecture with five neurons per layer (NL), and 15 numbers of layers (L). In general, the results obtained have shown an acceptable performance of the artificial neural network in the estimation of solar radiation, but with certain possibilities of being improved.","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"12 1","pages":"293-302"},"PeriodicalIF":0.0,"publicationDate":"2019-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41359182","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 : 2019-11-30DOI: 10.15866/ireaco.v12i6.17559
Hanene Rouabeh, C. Abdelmoula, M. Masmoudi
Road traffic safety has become a significant global public health issue. The number of traffic crashes is increasing in alarming proportions, leading to a large number of deaths and injuries. Most road accidents occur due to human errors including exceeding speed limit and failure to abide by driving rules. Therefore, in order to solve this issue, advanced driver-assistance systems are more and more in use thanks to their capabilities in minimizing the human error. These systems are used to enhance or adapt some or all of the tasks involved in operating a vehicle. Designers rely heavily on Artificial Intelligence in order to operate these systems. In this framework, this paper discusses the development of an intelligent speed limit signs’ recognition system, which can substantially enhance road safety. Since this system is conceived to be implanted on an FPGA card, the main challenges consist in achieving a high recognition rate with a low complexity level in the proposed algorithm. This will undoubtedly lead up to an optimized hardware architecture suitable for real time processing. For this purpose, a two-step based vision speed limit signs’ detection and recognition system has been proposed. The first step concerns sign candidate’s detection based on color and shape analysis; it consists in different sub image processing levels. The second step deals with the recognition and identification of the detected signs. To this end, several Machine Learning algorithms and several architectures of multilayer Neural Network and Wavelet Neural Network have been evaluated. The analysis of performance results and comparison with other widely used techniques have shown the effectiveness and efficiency of the proposed technique in terms of percentage of correct classification and execution time even for images captured under varied orientations and varied illumination conditions.
{"title":"An Intelligent Speed Limit Sign Recognition Approach Towards an Embedded Driver Assistance System","authors":"Hanene Rouabeh, C. Abdelmoula, M. Masmoudi","doi":"10.15866/ireaco.v12i6.17559","DOIUrl":"https://doi.org/10.15866/ireaco.v12i6.17559","url":null,"abstract":"Road traffic safety has become a significant global public health issue. The number of traffic crashes is increasing in alarming proportions, leading to a large number of deaths and injuries. Most road accidents occur due to human errors including exceeding speed limit and failure to abide by driving rules. Therefore, in order to solve this issue, advanced driver-assistance systems are more and more in use thanks to their capabilities in minimizing the human error. These systems are used to enhance or adapt some or all of the tasks involved in operating a vehicle. Designers rely heavily on Artificial Intelligence in order to operate these systems. In this framework, this paper discusses the development of an intelligent speed limit signs’ recognition system, which can substantially enhance road safety. Since this system is conceived to be implanted on an FPGA card, the main challenges consist in achieving a high recognition rate with a low complexity level in the proposed algorithm. This will undoubtedly lead up to an optimized hardware architecture suitable for real time processing. For this purpose, a two-step based vision speed limit signs’ detection and recognition system has been proposed. The first step concerns sign candidate’s detection based on color and shape analysis; it consists in different sub image processing levels. The second step deals with the recognition and identification of the detected signs. To this end, several Machine Learning algorithms and several architectures of multilayer Neural Network and Wavelet Neural Network have been evaluated. The analysis of performance results and comparison with other widely used techniques have shown the effectiveness and efficiency of the proposed technique in terms of percentage of correct classification and execution time even for images captured under varied orientations and varied illumination conditions.","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"12 1","pages":"281-292"},"PeriodicalIF":0.0,"publicationDate":"2019-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45182602","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 : 2019-05-31DOI: 10.15866/ireaco.v12i3.16455
Epyk Sunarno, Ramadhan Bilal Assidiq, Syechu Dwitya Nugraha, I. Sudiharto, O. Qudsi, Rachma Prilian Eviningsih
{"title":"Application of the Artificial Neural Network (ANN) Method as MPPT Photovoltaic for DC Source Storage","authors":"Epyk Sunarno, Ramadhan Bilal Assidiq, Syechu Dwitya Nugraha, I. Sudiharto, O. Qudsi, Rachma Prilian Eviningsih","doi":"10.15866/ireaco.v12i3.16455","DOIUrl":"https://doi.org/10.15866/ireaco.v12i3.16455","url":null,"abstract":"","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67286808","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 : 2018-09-30DOI: 10.15866/ireaco.v11i5.14781
Asma El Mekki, K. Ben Saad
{"title":"Discrete and Parametric Fault Diagnosis of an Inverter-Driven Brushless DC Motor Using a Hybrid Formalism","authors":"Asma El Mekki, K. Ben Saad","doi":"10.15866/ireaco.v11i5.14781","DOIUrl":"https://doi.org/10.15866/ireaco.v11i5.14781","url":null,"abstract":"","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67286771","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 : 2018-03-31DOI: 10.15866/IREACO.V11I2.13825
Mehdi Laraki, A. Hayar
In recent years, the role of street lighting has changed dramatically. Currently, street lighting is used not only to ensure the safety and comfort of citizens in a city, but also to make public spaces more attractive to pedestrians, cyclists, used cars, motorcycles, taxis and public transport, contributing to a more sustainable urban and rural future. On the other hand, public lighting is constantly increasing and polluting the environment (light pollution) as well as fauna. Yet, for some years now, the current QoS regulations oblige to sift the light, to use different methods and technologies to reduce the overexposure due to the light pollution as well as the energy consumption for a better comfort as the use of the sensors movements, automating lighting and other methods. The aim of this article is to show you how our proposed mathematical lighting model based on OFDM technique and our self-lighting concept, can reduce substantially the energy consumption. We propose to show our combined scheme and a complete study of energy gain calculation when pedestrian or vehicles detections are occurred in multispeed detections scenarios.
{"title":"Proposed Mathematical Lighting Model Based on OFDM Technique and Self-Lighting Concept for a Smart Lighting","authors":"Mehdi Laraki, A. Hayar","doi":"10.15866/IREACO.V11I2.13825","DOIUrl":"https://doi.org/10.15866/IREACO.V11I2.13825","url":null,"abstract":"In recent years, the role of street lighting has changed dramatically. Currently, street lighting is used not only to ensure the safety and comfort of citizens in a city, but also to make public spaces more attractive to pedestrians, cyclists, used cars, motorcycles, taxis and public transport, contributing to a more sustainable urban and rural future. On the other hand, public lighting is constantly increasing and polluting the environment (light pollution) as well as fauna. Yet, for some years now, the current QoS regulations oblige to sift the light, to use different methods and technologies to reduce the overexposure due to the light pollution as well as the energy consumption for a better comfort as the use of the sensors movements, automating lighting and other methods. The aim of this article is to show you how our proposed mathematical lighting model based on OFDM technique and our self-lighting concept, can reduce substantially the energy consumption. We propose to show our combined scheme and a complete study of energy gain calculation when pedestrian or vehicles detections are occurred in multispeed detections scenarios.","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"11 1","pages":"77-85"},"PeriodicalIF":0.0,"publicationDate":"2018-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42674416","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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