Pub Date : 2021-01-31DOI: 10.15866/IREACO.V14I1.18710
Endo Kristiyono, A. S. Girsang
Indonesia is one of the world’s richest nations in biodiversity. Genetic resources management features a wide range of activities involving various agencies and organizations. Nowadays, data and information on genetic and biodiversity resources are still unintegrated between agencies and institutions. This causes a situation called information silo, which leads to management information systems being ineffective and inefficient. In order to overcome this problem, a flexible, interoperable architecture control is needed. Service-Oriented Architecture (SOA) is an appropriate approach to control distributed and heterogeneous systems to integrate genetic resources data and information systems at the Indonesian Agency for Agricultural Research and Development (IAARD). The SOA system is built by the SOMA method, which consists of some methods. The results show that the new system runs well and it is more effective and efficient than the previous one.
{"title":"Controlling Biodiversity Data in the Agricultural Gene Bank Using Service-Oriented Architecture","authors":"Endo Kristiyono, A. S. Girsang","doi":"10.15866/IREACO.V14I1.18710","DOIUrl":"https://doi.org/10.15866/IREACO.V14I1.18710","url":null,"abstract":"Indonesia is one of the world’s richest nations in biodiversity. Genetic resources management features a wide range of activities involving various agencies and organizations. Nowadays, data and information on genetic and biodiversity resources are still unintegrated between agencies and institutions. This causes a situation called information silo, which leads to management information systems being ineffective and inefficient. In order to overcome this problem, a flexible, interoperable architecture control is needed. Service-Oriented Architecture (SOA) is an appropriate approach to control distributed and heterogeneous systems to integrate genetic resources data and information systems at the Indonesian Agency for Agricultural Research and Development (IAARD). The SOA system is built by the SOMA method, which consists of some methods. The results show that the new system runs well and it is more effective and efficient than the previous one.","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"14 1","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2021-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42162321","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 : 2021-01-31DOI: 10.15866/IREACO.V14I1.20057
A. Bataineh, Wafa Batayneh, M. Okour
Suspension system plays a major role in both comfort and stability of a vehicle. This paper presents modeling and controlling for a 3 Degree of Freedom (DOF) active suspension system. Four controllers are designed to control the response of the active suspension system, namely PID, LQR, Fuzzy Logic Controller (FLC) and Artificial Neural Network (ANN). The response for both the active suspension system and the passive suspension system is compared. For passive suspension system, it has been found out that it is hard to improve both passenger comfort and road handling at the same time, because of the fixed parameters that cannot be changed during the work. On the other hand, in active suspension system, both ride comfort and road handling can be improved. This work has showed that ANN, FLC, LQR, and PID controllers can be used with an active suspension system in order to improve the performance, the stability, and the ride comfortability compared to the passive suspension system. All these controllers are simulated using MATLAB and Simulink. Different road profiles are used to test the active suspension system response, such as a step input of 0.1 m, and a sinewave of amplitude of 0.3m and a frequency of 0.318Hz. All the controllers show better response compared to passive suspension system. A compromise can be done to choose the controller depending on the desired states.
{"title":"Intelligent Control Strategies for Three Degree of Freedom Active Suspension System","authors":"A. Bataineh, Wafa Batayneh, M. Okour","doi":"10.15866/IREACO.V14I1.20057","DOIUrl":"https://doi.org/10.15866/IREACO.V14I1.20057","url":null,"abstract":"Suspension system plays a major role in both comfort and stability of a vehicle. This paper presents modeling and controlling for a 3 Degree of Freedom (DOF) active suspension system. Four controllers are designed to control the response of the active suspension system, namely PID, LQR, Fuzzy Logic Controller (FLC) and Artificial Neural Network (ANN). The response for both the active suspension system and the passive suspension system is compared. For passive suspension system, it has been found out that it is hard to improve both passenger comfort and road handling at the same time, because of the fixed parameters that cannot be changed during the work. On the other hand, in active suspension system, both ride comfort and road handling can be improved. This work has showed that ANN, FLC, LQR, and PID controllers can be used with an active suspension system in order to improve the performance, the stability, and the ride comfortability compared to the passive suspension system. All these controllers are simulated using MATLAB and Simulink. Different road profiles are used to test the active suspension system response, such as a step input of 0.1 m, and a sinewave of amplitude of 0.3m and a frequency of 0.318Hz. All the controllers show better response compared to passive suspension system. A compromise can be done to choose the controller depending on the desired states.","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"14 1","pages":"17-27"},"PeriodicalIF":0.0,"publicationDate":"2021-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48691728","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 : 2020-11-30DOI: 10.15866/IREACO.V13I6.19331
J. Cárdenas, Edwin Espinel, J. P. Rojas
Quality control methodologies and improvement methods have been applied to the process management in order to develop a set of fault diagnosis practices during the industrial operation of mechanical components in production lines. These practices are based on the reliability concept, which defines the failure probability due to the building or design processes and maintenance activities. In this sense, a quality methodology may be considered a powerful tool employed to determine the main causes of the recurring failure events associated with the downtime cost and the material losses during the industrial production. A quality function development may be conformed by four main phases: scheme design, components definition, engineering and quality control, and manufacturing work order. Taking into account the above, this paper proposes a quality function deployment method in order to define the appropriate control parameters, which define the needs of the specific production processes related to the functionality of the mechanical devices or the minimal requirements where inspection, test specifications, and failure diagnosis are developed. In this sense, this paper purposes a quality function development methodology in order to analyze the failure analysis of the pressure–control valve implemented in a hydraulic system to verify the possible causes of non-conformity and to define a set of alternatives that improve the production process. This decision-making problem has been based on two steps: strategic and operational terms, where each point has been resolved to define a successful development of this quality control methodology. The qualitative assessment of this particular study identifies a containment loss of the pressure-control valve used to maintain the reactor oil level in the hydraulic system.
{"title":"Failure Analysis Methodology in Industrial Control Valves Using Quality Function","authors":"J. Cárdenas, Edwin Espinel, J. P. Rojas","doi":"10.15866/IREACO.V13I6.19331","DOIUrl":"https://doi.org/10.15866/IREACO.V13I6.19331","url":null,"abstract":"Quality control methodologies and improvement methods have been applied to the process management in order to develop a set of fault diagnosis practices during the industrial operation of mechanical components in production lines. These practices are based on the reliability concept, which defines the failure probability due to the building or design processes and maintenance activities. In this sense, a quality methodology may be considered a powerful tool employed to determine the main causes of the recurring failure events associated with the downtime cost and the material losses during the industrial production. A quality function development may be conformed by four main phases: scheme design, components definition, engineering and quality control, and manufacturing work order. Taking into account the above, this paper proposes a quality function deployment method in order to define the appropriate control parameters, which define the needs of the specific production processes related to the functionality of the mechanical devices or the minimal requirements where inspection, test specifications, and failure diagnosis are developed. In this sense, this paper purposes a quality function development methodology in order to analyze the failure analysis of the pressure–control valve implemented in a hydraulic system to verify the possible causes of non-conformity and to define a set of alternatives that improve the production process. This decision-making problem has been based on two steps: strategic and operational terms, where each point has been resolved to define a successful development of this quality control methodology. The qualitative assessment of this particular study identifies a containment loss of the pressure-control valve used to maintain the reactor oil level in the hydraulic system.","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"13 1","pages":"273"},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42991770","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 : 2020-11-30DOI: 10.15866/IREACO.V13I6.20017
Luu Thi Hue, Nguyễn Phạm Thục Anh, D. M. Duc
The paper has developed an adaptive hybrid force/position control scheme using neural network observer for controlling dual-arm robotic system considering system uncertainties. Firstly, an overall dynamics of the system including the manipulators and the object are derived using Euler-Lagrangian principle. Then, a neural-adaptive observer is designed to estimate the object velocities using a radial basis neural network. Based on the observed velocities, an adaptive hybrid force/position controller is proposed to compensate dynamic uncertainties without force measurement. The neuro-adaptive observer and the controller learning algorithms have been derived according to Lyapunov stability principle in order to guarantee asymptotical convergence of the closed loop system. Finally, simulation work has been carried out to validate the accuracy and the effectiveness of the proposed approach.
{"title":"Adaptive Hybrid Force/Position Control Using Neuro-Adaptive Observer for Dual-Arm Robot","authors":"Luu Thi Hue, Nguyễn Phạm Thục Anh, D. M. Duc","doi":"10.15866/IREACO.V13I6.20017","DOIUrl":"https://doi.org/10.15866/IREACO.V13I6.20017","url":null,"abstract":"The paper has developed an adaptive hybrid force/position control scheme using neural network observer for controlling dual-arm robotic system considering system uncertainties. Firstly, an overall dynamics of the system including the manipulators and the object are derived using Euler-Lagrangian principle. Then, a neural-adaptive observer is designed to estimate the object velocities using a radial basis neural network. Based on the observed velocities, an adaptive hybrid force/position controller is proposed to compensate dynamic uncertainties without force measurement. The neuro-adaptive observer and the controller learning algorithms have been derived according to Lyapunov stability principle in order to guarantee asymptotical convergence of the closed loop system. Finally, simulation work has been carried out to validate the accuracy and the effectiveness of the proposed approach.","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"13 1","pages":"313-328"},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44562429","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 : 2020-11-30DOI: 10.15866/IREACO.V13I6.19440
L. Obolenskaya, E. Moreva, T. Sakulyeva, V. Druzyanova
The intellectualization of transportation system is a relevant task for solving traffic-related problems such as vehicle traffic management and modern transport system improvement. The purpose of this work was to design a competitive pathway for real transport system to optimize the route planning. Modeling of the transport system refers to the problem of finding the K-shortest sustainable pathway in a multimodal network. The solution to this problem was fulfilled by applying a hybrid algorithm of an ant colony based on a differential evolution approach to the pheromone renewal and the division of the colony into teams. Experimental results showed that an advanced ants colony algorithm is highly efficient even with quite a small population of the colony. The obtained results were compared with those of the conventional ant colony algorithm. Due to its high efficiency, the elaborated method is applicable in improving the quality of the entire road network, especially in congestions and traffic jams, taking into account real-time traffic information.
{"title":"Traffic Forecast Based on Statistical Data for Public Transport Optimization in Real Time","authors":"L. Obolenskaya, E. Moreva, T. Sakulyeva, V. Druzyanova","doi":"10.15866/IREACO.V13I6.19440","DOIUrl":"https://doi.org/10.15866/IREACO.V13I6.19440","url":null,"abstract":"The intellectualization of transportation system is a relevant task for solving traffic-related problems such as vehicle traffic management and modern transport system improvement. The purpose of this work was to design a competitive pathway for real transport system to optimize the route planning. Modeling of the transport system refers to the problem of finding the K-shortest sustainable pathway in a multimodal network. The solution to this problem was fulfilled by applying a hybrid algorithm of an ant colony based on a differential evolution approach to the pheromone renewal and the division of the colony into teams. Experimental results showed that an advanced ants colony algorithm is highly efficient even with quite a small population of the colony. The obtained results were compared with those of the conventional ant colony algorithm. Due to its high efficiency, the elaborated method is applicable in improving the quality of the entire road network, especially in congestions and traffic jams, taking into account real-time traffic information.","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"13 1","pages":"264-272"},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48439861","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 : 2020-11-30DOI: 10.15866/IREACO.V13I6.19148
G. Prada, J. P. Rojas, G. Romero
This paper presents the design and the performance comparison of a classic PID controller, a feedforward PID controller, and a fuzzy PID controller. These controllers have been implemented to control the outlet temperature of a shell and tube heat exchanger. The controller with feedforward is proposed to provide assistance in the closed-loop control, in order to reduce the disturbances that affect the system. This method is compared with the fuzzy one, which is based on the concepts of artificial intelligence, genetic algorithm, neural networks, and fuzzy logic. For this controller, Gaussian membership functions have been established, a universe of discourse ranging from -6 to 6 for the error and its derivative, and a universe of discourse ranging from -0.5 to 0.5 for the control variables. From the results of this study, it has been concluded that the tracking error in the output temperature under the variation of the set-point decreases in a faster way in the PID with feedforward respect to the classical PID. However, the fuzzy adaptive PID control is based on the optimized parameters.
{"title":"Fuzzy Adaptive PID Control of a Shell and Tube Heat Exchanger Output Temperature","authors":"G. Prada, J. P. Rojas, G. Romero","doi":"10.15866/IREACO.V13I6.19148","DOIUrl":"https://doi.org/10.15866/IREACO.V13I6.19148","url":null,"abstract":"This paper presents the design and the performance comparison of a classic PID controller, a feedforward PID controller, and a fuzzy PID controller. These controllers have been implemented to control the outlet temperature of a shell and tube heat exchanger. The controller with feedforward is proposed to provide assistance in the closed-loop control, in order to reduce the disturbances that affect the system. This method is compared with the fuzzy one, which is based on the concepts of artificial intelligence, genetic algorithm, neural networks, and fuzzy logic. For this controller, Gaussian membership functions have been established, a universe of discourse ranging from -6 to 6 for the error and its derivative, and a universe of discourse ranging from -0.5 to 0.5 for the control variables. From the results of this study, it has been concluded that the tracking error in the output temperature under the variation of the set-point decreases in a faster way in the PID with feedforward respect to the classical PID. However, the fuzzy adaptive PID control is based on the optimized parameters.","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"13 1","pages":"283"},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44548631","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 : 2020-11-30DOI: 10.15866/IREACO.V13I6.17354
Abdennacer Ben Messaoud, S. Talmoudi, M. Ksouri
In order to deal with some difficult problems in fractional-order systems, like high computational load of fractional-order operator, fractional-order transfer function is commonly approximated by an integer order model. However, the dimension of this model increases with its accuracy, which can make the design of a controller more difficult. In this paper, a new approach for modelling of fractional-order systems is investigated. Exploiting the multimodel technique, the suggested method replaces the unique fractional-order model by a set of simpler integer order models. The determination of the different models is based on an approximation of the fractional-order derivative operator sα. Then the global model is obtained through a fusion of the simple models weighted by their respective relevance degrees calculated by optimizing a constrained least squares problem. The resulting final model can represent adequately the fractional-order systems both in time and in frequency domains. Simulations and comparative studies carried out on academic examples indicate the interest, the clarity and the improvement in accuracy in both time and frequency domains of the proposed modelling method, compared to modelling by a single model based on the approximation of Oustaloup.
{"title":"A New Multimodel Representation of Fractional-Order Systems in Both Time and Frequency Domains","authors":"Abdennacer Ben Messaoud, S. Talmoudi, M. Ksouri","doi":"10.15866/IREACO.V13I6.17354","DOIUrl":"https://doi.org/10.15866/IREACO.V13I6.17354","url":null,"abstract":"In order to deal with some difficult problems in fractional-order systems, like high computational load of fractional-order operator, fractional-order transfer function is commonly approximated by an integer order model. However, the dimension of this model increases with its accuracy, which can make the design of a controller more difficult. In this paper, a new approach for modelling of fractional-order systems is investigated. Exploiting the multimodel technique, the suggested method replaces the unique fractional-order model by a set of simpler integer order models. The determination of the different models is based on an approximation of the fractional-order derivative operator sα. Then the global model is obtained through a fusion of the simple models weighted by their respective relevance degrees calculated by optimizing a constrained least squares problem. The resulting final model can represent adequately the fractional-order systems both in time and in frequency domains. Simulations and comparative studies carried out on academic examples indicate the interest, the clarity and the improvement in accuracy in both time and frequency domains of the proposed modelling method, compared to modelling by a single model based on the approximation of Oustaloup.","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"13 1","pages":"292-303"},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43899131","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 : 2020-11-30DOI: 10.15866/IREACO.V13I6.19841
Mahmoud Essam M. Harby, Helmy Elzoghby, S. Elmasry, A. Elsamahy
{"title":"Bidirectional Control of Electric Vehicles Based on Artificial Neural Network Considering Owners Convenience and Microgrid Stability","authors":"Mahmoud Essam M. Harby, Helmy Elzoghby, S. Elmasry, A. Elsamahy","doi":"10.15866/IREACO.V13I6.19841","DOIUrl":"https://doi.org/10.15866/IREACO.V13I6.19841","url":null,"abstract":"","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"13 1","pages":"304"},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48459011","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 : 2020-09-30DOI: 10.15866/ireaco.v13i5.19212
Joshua Sunder David Reddipogu, Vinodh Kumar Elumalai
This paper puts forward a multi-objective model predictive control scheme in order to address the conflicting control objectives of a vehicle active suspension system. The key problem in designing an active suspension controller is that the controller has to realize a feasible control input that can satisfy the competing control requirements such as ride comfort, suspension travel and road handling. Hence, in this work, these constraints are integrated into an optimal control framework and a finite horizon model predictive controller is used to solve the multi-objective cost function. The key advantage of the proposed scheme is that the model predictive control design finds the optimal control input by solving the discrete time algebraic Riccati equation. This guarantees not only a robust closed loop system but also a realizable control effort, without violating the hard constraints of the active suspension system. The proposed model predictive control design is experimentally validated on a laboratory scale quarter car suspension system using hardware-in-loop testing. The performance of the model predictive control scheme is compared with the one of the unconstrained linear quadratic regulator and tested for four realistic road profiles. The experimental results substantiate that the suspension system controlled by the model predictive controller offers better ride comfort and road handling features when compared to the conventional linear quadratic regulator.
{"title":"Multi-Objective Model Predictive Control for Vehicle Active Suspension System","authors":"Joshua Sunder David Reddipogu, Vinodh Kumar Elumalai","doi":"10.15866/ireaco.v13i5.19212","DOIUrl":"https://doi.org/10.15866/ireaco.v13i5.19212","url":null,"abstract":"This paper puts forward a multi-objective model predictive control scheme in order to address the conflicting control objectives of a vehicle active suspension system. The key problem in designing an active suspension controller is that the controller has to realize a feasible control input that can satisfy the competing control requirements such as ride comfort, suspension travel and road handling. Hence, in this work, these constraints are integrated into an optimal control framework and a finite horizon model predictive controller is used to solve the multi-objective cost function. The key advantage of the proposed scheme is that the model predictive control design finds the optimal control input by solving the discrete time algebraic Riccati equation. This guarantees not only a robust closed loop system but also a realizable control effort, without violating the hard constraints of the active suspension system. The proposed model predictive control design is experimentally validated on a laboratory scale quarter car suspension system using hardware-in-loop testing. The performance of the model predictive control scheme is compared with the one of the unconstrained linear quadratic regulator and tested for four realistic road profiles. The experimental results substantiate that the suspension system controlled by the model predictive controller offers better ride comfort and road handling features when compared to the conventional linear quadratic regulator.","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"13 1","pages":"255-263"},"PeriodicalIF":0.0,"publicationDate":"2020-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45560655","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 : 2020-09-30DOI: 10.15866/ireaco.v13i5.19379
Mahmoud Essam M. Harby, Helmy Elzoghby, S. Elmasry, A. A. El-Samahy
The large-scale renewable energy contribution tends to expand vastly; this is due to the numerous benefits of the renewable energy from the environmental and economic aspects. From another hand, renewable resources are intermittent and changeable in nature, which would affect the microgrid frequency stability. In this paper, a fully renewable and green microgrid is proposed aiming to zero emission power generation, the microgrid consists of Biogas plant, Biodiesel plant, Photovoltaic system, Wind turbines, Battery Energy Storage System and Electric Vehicles. The main contribution of this paper is providing the frequency stability enhancement of the microgrid through controlling the charging and discharging of the electric vehicles batteries using fuzzy logic controller based on three main factors, the electric vehicle battery state of charge, the microgrid frequency deviation signal and the departure time of the vehicle, which is set in advance by the owner. The enhancement of the frequency is performed without using extra storage system. This work is providing two main scenarios for the frequency stability enhancement, the first one is through controlling only the charging of the electric vehicles batteries and the second one is done through controlling the charging and discharging of the electric vehicles batteries as going to be presented a head.
{"title":"Microgrid Frequency Stability Enhancement Through Controlling Electric Vehicles Batteries Based on Fuzzy Logic Controller","authors":"Mahmoud Essam M. Harby, Helmy Elzoghby, S. Elmasry, A. A. El-Samahy","doi":"10.15866/ireaco.v13i5.19379","DOIUrl":"https://doi.org/10.15866/ireaco.v13i5.19379","url":null,"abstract":"The large-scale renewable energy contribution tends to expand vastly; this is due to the numerous benefits of the renewable energy from the environmental and economic aspects. From another hand, renewable resources are intermittent and changeable in nature, which would affect the microgrid frequency stability. In this paper, a fully renewable and green microgrid is proposed aiming to zero emission power generation, the microgrid consists of Biogas plant, Biodiesel plant, Photovoltaic system, Wind turbines, Battery Energy Storage System and Electric Vehicles. The main contribution of this paper is providing the frequency stability enhancement of the microgrid through controlling the charging and discharging of the electric vehicles batteries using fuzzy logic controller based on three main factors, the electric vehicle battery state of charge, the microgrid frequency deviation signal and the departure time of the vehicle, which is set in advance by the owner. The enhancement of the frequency is performed without using extra storage system. This work is providing two main scenarios for the frequency stability enhancement, the first one is through controlling only the charging of the electric vehicles batteries and the second one is done through controlling the charging and discharging of the electric vehicles batteries as going to be presented a head.","PeriodicalId":38433,"journal":{"name":"International Review of Automatic Control","volume":"13 1","pages":"214"},"PeriodicalIF":0.0,"publicationDate":"2020-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41966748","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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