A novel blended state estimated adaptive controller is designed for voltage and current control of microgrid against unknown noise. The state of a microgrid can deteriorate due to disturbances and packet losses. Therefore, it is necessary to achieve the true state of the system to enhance the control requirement and automation of the microgrid. To achieve the true state, this study proposes an unscented kalman filter algorithm. This algorithm is developed using an unscented-transformation and sigma-points measurement technique capable of minimizing the mean and covariance of a nonlinear cost function to estimate the true state of microgrid system. The effectiveness of the proposed algorithm is compared with an extended kalman filter. A model-reference modified adaptive PID controller is also developed and used in conjunction with the system to control its voltage and current. The performance of the developed controller is also evaluated against a certain number of load dynamics. Results indicate the controller provides more stable and high-tracking performance with the inclusion of the UKF in the system.
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Abu Bakar Siddique was born in Chandpur, Bangladesh. He has completed his B.Sc. engineering under the department of Mechatronics Engineering from Rajshahi University of Engineering & Technology (RUET), Rajshahi, Bangladesh. His research interest includes Control Theory and Applications.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A novel blended state estimated adaptive controller is designed for voltage and current control of microgrid against unknown noise. The state of a microgrid can deteriorate due to disturbances and packet losses. Therefore, it is necessary to achieve the true state of the system to enhance the control requirement and automation of the microgrid. To achieve the true state, this study proposes an unscented kalman filter algorithm. This algorithm is developed using an unscented-transformation and sigma-points measurement technique capable of minimizing the mean and covariance of a nonlinear cost function to estimate the true state of microgrid system. The effectiveness of the proposed algorithm is compared with an extended kalman filter. A model-reference modified adaptive PID controller is also developed and used in conjunction with the system to control its voltage and current. The performance of the developed controller is also evaluated against a certain number of load dynamics. Results indicate the controller provides more stable and high-tracking performance with the inclusion of the UKF in the system. 104 pp. Englisch. Bestandsnummer des Verkäufers 9786200229908
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Siddique Abu BakarAbu Bakar Siddique was born in Chandpur, Bangladesh. He has completed his B.Sc. engineering under the department of Mechatronics Engineering from Rajshahi University of Engineering & Technology (RUET), Rajshahi,. Bestandsnummer des Verkäufers 385885663
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -A novel blended state estimated adaptive controller is designed for voltage and current control of microgrid against unknown noise. The state of a microgrid can deteriorate due to disturbances and packet losses. Therefore, it is necessary to achieve the true state of the system to enhance the control requirement and automation of the microgrid. To achieve the true state, this study proposes an unscented kalman filter algorithm. This algorithm is developed using an unscented-transformation and sigma-points measurement technique capable of minimizing the mean and covariance of a nonlinear cost function to estimate the true state of microgrid system. The effectiveness of the proposed algorithm is compared with an extended kalman filter. A model-reference modified adaptive PID controller is also developed and used in conjunction with the system to control its voltage and current. The performance of the developed controller is also evaluated against a certain number of load dynamics. Results indicate the controller provides more stable and high-tracking performance with the inclusion of the UKF in the system.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 104 pp. Englisch. Bestandsnummer des Verkäufers 9786200229908
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A novel blended state estimated adaptive controller is designed for voltage and current control of microgrid against unknown noise. The state of a microgrid can deteriorate due to disturbances and packet losses. Therefore, it is necessary to achieve the true state of the system to enhance the control requirement and automation of the microgrid. To achieve the true state, this study proposes an unscented kalman filter algorithm. This algorithm is developed using an unscented-transformation and sigma-points measurement technique capable of minimizing the mean and covariance of a nonlinear cost function to estimate the true state of microgrid system. The effectiveness of the proposed algorithm is compared with an extended kalman filter. A model-reference modified adaptive PID controller is also developed and used in conjunction with the system to control its voltage and current. The performance of the developed controller is also evaluated against a certain number of load dynamics. Results indicate the controller provides more stable and high-tracking performance with the inclusion of the UKF in the system. Bestandsnummer des Verkäufers 9786200229908
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Taschenbuch. Zustand: Neu. State Estimated Adaptive Controller Design for Microgrid Control | A novel approach to estimate the state of microgrid and control of voltage and current against unknown noise | Abu Bakar Siddique (u. a.) | Taschenbuch | 104 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786200229908 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 117560314
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