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Browsing by Author "Simani, Silvio"

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    Citation - WoS: 3
    Citation - Scopus: 3
    Design and Validation of a Fault Tolerant Fuzzy Control for a Wind Park High-Fidelity Simulator
    (Ieee, 2021) Simani, Silvio; Turhan, Cihan; Farsoni, Saverio
    To enhance both the safety and the efficiency of offshore wind park systems, faults must be accommodated in their earlier occurrence, in order to avoid costly unplanned maintenance. Therefore, this paper aims at implementing a fault tolerant control strategy by means of a data-driven approach relying on fuzzy logic. In particular, fuzzy modelling is considered here as it enables to approximate unknown nonlinear relations, while managing uncertain measurements and disturbance. On the other hand, the model of the fuzzy controller is directly estimated from the input-output signals acquired from the wind farm system, with fault tolerant capabilities. In general, the use of purely nonlinear relations and analytic methods would require more complex design tools. The design is therefore enhanced by the use of fuzzy model prototypes obtained via a data-driven approach, thus representing the key point if real-time solutions have to implement the proposed fault tolerant control strategy. Finally, a high-fidelity simulator including hardware-in-the-loop modules is exploited to validate the reliability and robustness characteristics of the developed methodologies also for on-line implementations.
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    Citation - WoS: 33
    Citation - Scopus: 41
    Development of a Personalized Thermal Comfort Driven Controller for Hvac Systems
    (Pergamon-elsevier Science Ltd, 2021) Turhan, Cihan; Simani, Silvio; Akkurt, Gulden Gokcen
    Increasing thermal comfort and reducing energy consumption are two main objectives of advanced HVAC control systems. In this study, a thermal comfort driven control (PTC-DC) algorithm was developed to improve HVAC control systems with no need of retrofitting HVAC system components. A case building located in Izmir Institute of Technology Campus-Izmir-Turkey was selected to test the developed system. First, wireless sensors were installed to the building and a mobile application was developed to monitor/ collect temperature, relative humidity and thermal comfort data of an occupant. Then, the PTC-DC algorithm was developed to meet the highest occupant thermal comfort as well as saving energy. The prototypes of the controller were tested on the case building from July 3rd, 2017 to November 1st, 2018 and compared with a conventional PID controller. The results showed that the developed control algorithm and conventional controller satisfy neutral thermal comfort for 92 % and 6 % of total measurement days, respectively. From energy consumption point of view, the PTC-DC decreased energy consumption by 13.2 % compared to the conventional controller. Consequently, the PTC-DC differs from other works in the literature that the prototype of PTC-DC can be easily deployed in real environments. Moreover, the PTC-DC is low-cost and user-friendly. (c) 2021 Elsevier Ltd. All rights reserved.
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    Citation - WoS: 1
    Citation - Scopus: 2
    Hardware-In Assessment of a Fault Tolerant Fuzzy Control Scheme for an Offshore Wind Farm Simulator
    (Elsevier, 2022) Simani, Silvio; Farsoni, Saverio; Turhan, Cihan
    To enhance both the safety and the efficiency of offshore wind park systems, faults must be accommodated in their earlier occurrence, in order to avoid costly unplanned maintenance. Therefore, this paper aims at implementing a fault tolerant control strategy by means of a data-driven approach relying on fuzzy logic. In particular, fuzzy modelling is considered here as it enables to approximate unknown nonlinear relations, while managing uncertain measurements and disturbance. On the other hand, the model of the fuzzy controller is directly estimated from the input-output signals acquired from the wind farm system, with fault tolerant capabilities. In general, the use of purely nonlinear relations and analytic methods would require more complex design tools. The design is therefore enhanced by the use of fuzzy model prototypes obtained via a data-driven approach, thus representing the key point if real-time solutions have to implement the proposed fault tolerant control strategy. Finally, a high-fidelity simulator relying on a hardware-in-the-loop tool is exploited to verify and validate the reliability and robustness characteristics of the developed methodology also for on-line and more realistic implementations. Copyright (C) 2022 The Authors.
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