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You searched for +publisher:"Rochester Institute of Technology" +contributor:("Abdulla Ismail"). Showing records 1 – 8 of 8 total matches.

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Rochester Institute of Technology

1. Khallaf, Mohamed. Enhanced MPPT Controllers for Smart Grid Applications.

Degree: MS, Electrical Engineering, 2019, Rochester Institute of Technology

  Over the past years, the energy demand has been steadily growing and so methods of how to cope with this staggering increase are being… (more)

Subjects/Keywords: Fuzzy logic; Incremental conductance; MPPT; P&O; PV; Renewable energy

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APA (6th Edition):

Khallaf, M. (2019). Enhanced MPPT Controllers for Smart Grid Applications. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/10018

Chicago Manual of Style (16th Edition):

Khallaf, Mohamed. “Enhanced MPPT Controllers for Smart Grid Applications.” 2019. Masters Thesis, Rochester Institute of Technology. Accessed December 03, 2020. https://scholarworks.rit.edu/theses/10018.

MLA Handbook (7th Edition):

Khallaf, Mohamed. “Enhanced MPPT Controllers for Smart Grid Applications.” 2019. Web. 03 Dec 2020.

Vancouver:

Khallaf M. Enhanced MPPT Controllers for Smart Grid Applications. [Internet] [Masters thesis]. Rochester Institute of Technology; 2019. [cited 2020 Dec 03]. Available from: https://scholarworks.rit.edu/theses/10018.

Council of Science Editors:

Khallaf M. Enhanced MPPT Controllers for Smart Grid Applications. [Masters Thesis]. Rochester Institute of Technology; 2019. Available from: https://scholarworks.rit.edu/theses/10018


Rochester Institute of Technology

2. AlMarri, Salem Bin Saqer. Real-Time Facial Emotion Recognition Using Fast R-CNN.

Degree: MS, Electrical Engineering, 2019, Rochester Institute of Technology

  In computer vision and image processing, object detection algorithms are used to detect semantic objects of certain classes of images and videos. Object detector… (more)

Subjects/Keywords: Artificial intelligence; Convolutional neural network; Facial emotion recognition

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APA (6th Edition):

AlMarri, S. B. S. (2019). Real-Time Facial Emotion Recognition Using Fast R-CNN. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/10214

Chicago Manual of Style (16th Edition):

AlMarri, Salem Bin Saqer. “Real-Time Facial Emotion Recognition Using Fast R-CNN.” 2019. Masters Thesis, Rochester Institute of Technology. Accessed December 03, 2020. https://scholarworks.rit.edu/theses/10214.

MLA Handbook (7th Edition):

AlMarri, Salem Bin Saqer. “Real-Time Facial Emotion Recognition Using Fast R-CNN.” 2019. Web. 03 Dec 2020.

Vancouver:

AlMarri SBS. Real-Time Facial Emotion Recognition Using Fast R-CNN. [Internet] [Masters thesis]. Rochester Institute of Technology; 2019. [cited 2020 Dec 03]. Available from: https://scholarworks.rit.edu/theses/10214.

Council of Science Editors:

AlMarri SBS. Real-Time Facial Emotion Recognition Using Fast R-CNN. [Masters Thesis]. Rochester Institute of Technology; 2019. Available from: https://scholarworks.rit.edu/theses/10214


Rochester Institute of Technology

3. Al-Zabin, Omar. Rotor Current Control Design for DFIG-based Wind Turbine Using PI, FLC and Fuzzy PI Controllers.

Degree: MS, Electrical Engineering, 2019, Rochester Institute of Technology

  Due to the rising demand for electricity with increasing world population, maximizing renewable energy capture through efficient control systems is gaining attention in literature.… (more)

Subjects/Keywords: DFIG-based wind turbine; Fuzzy PI controllers; Rotor current control

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APA (6th Edition):

Al-Zabin, O. (2019). Rotor Current Control Design for DFIG-based Wind Turbine Using PI, FLC and Fuzzy PI Controllers. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/10325

Chicago Manual of Style (16th Edition):

Al-Zabin, Omar. “Rotor Current Control Design for DFIG-based Wind Turbine Using PI, FLC and Fuzzy PI Controllers.” 2019. Masters Thesis, Rochester Institute of Technology. Accessed December 03, 2020. https://scholarworks.rit.edu/theses/10325.

MLA Handbook (7th Edition):

Al-Zabin, Omar. “Rotor Current Control Design for DFIG-based Wind Turbine Using PI, FLC and Fuzzy PI Controllers.” 2019. Web. 03 Dec 2020.

Vancouver:

Al-Zabin O. Rotor Current Control Design for DFIG-based Wind Turbine Using PI, FLC and Fuzzy PI Controllers. [Internet] [Masters thesis]. Rochester Institute of Technology; 2019. [cited 2020 Dec 03]. Available from: https://scholarworks.rit.edu/theses/10325.

Council of Science Editors:

Al-Zabin O. Rotor Current Control Design for DFIG-based Wind Turbine Using PI, FLC and Fuzzy PI Controllers. [Masters Thesis]. Rochester Institute of Technology; 2019. Available from: https://scholarworks.rit.edu/theses/10325


Rochester Institute of Technology

4. Naghshineh, Nastaran. Control of Thermal Power System Using Adaptive Fuzzy Logic Control.

Degree: MS, Electrical Engineering, 2017, Rochester Institute of Technology

  Controlling thermal power systems increases the overall system efficiency and satisfies the desired requirements. In such a large system, fuel reduction of even a… (more)

Subjects/Keywords: Adaptive fuzzy logic control; Control; Fuzzy logic; Multi-area power system; PID; Thermal power system

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APA (6th Edition):

Naghshineh, N. (2017). Control of Thermal Power System Using Adaptive Fuzzy Logic Control. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/9615

Chicago Manual of Style (16th Edition):

Naghshineh, Nastaran. “Control of Thermal Power System Using Adaptive Fuzzy Logic Control.” 2017. Masters Thesis, Rochester Institute of Technology. Accessed December 03, 2020. https://scholarworks.rit.edu/theses/9615.

MLA Handbook (7th Edition):

Naghshineh, Nastaran. “Control of Thermal Power System Using Adaptive Fuzzy Logic Control.” 2017. Web. 03 Dec 2020.

Vancouver:

Naghshineh N. Control of Thermal Power System Using Adaptive Fuzzy Logic Control. [Internet] [Masters thesis]. Rochester Institute of Technology; 2017. [cited 2020 Dec 03]. Available from: https://scholarworks.rit.edu/theses/9615.

Council of Science Editors:

Naghshineh N. Control of Thermal Power System Using Adaptive Fuzzy Logic Control. [Masters Thesis]. Rochester Institute of Technology; 2017. Available from: https://scholarworks.rit.edu/theses/9615

5. Emara, Samar. Control of PV Connected Power Grid using LQR and Fuzzy Logic Control.

Degree: MS, Electrical Engineering, 2018, Rochester Institute of Technology

  As the contribution of renewable energy to the current power grid is becoming an essential part of the global energy system, it is of… (more)

Subjects/Keywords: Feedback control; Fuzzy logic; Linear quadratic regulator; Load frequency control; Photovoltaic; Power system

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APA (6th Edition):

Emara, S. (2018). Control of PV Connected Power Grid using LQR and Fuzzy Logic Control. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/9734

Chicago Manual of Style (16th Edition):

Emara, Samar. “Control of PV Connected Power Grid using LQR and Fuzzy Logic Control.” 2018. Masters Thesis, Rochester Institute of Technology. Accessed December 03, 2020. https://scholarworks.rit.edu/theses/9734.

MLA Handbook (7th Edition):

Emara, Samar. “Control of PV Connected Power Grid using LQR and Fuzzy Logic Control.” 2018. Web. 03 Dec 2020.

Vancouver:

Emara S. Control of PV Connected Power Grid using LQR and Fuzzy Logic Control. [Internet] [Masters thesis]. Rochester Institute of Technology; 2018. [cited 2020 Dec 03]. Available from: https://scholarworks.rit.edu/theses/9734.

Council of Science Editors:

Emara S. Control of PV Connected Power Grid using LQR and Fuzzy Logic Control. [Masters Thesis]. Rochester Institute of Technology; 2018. Available from: https://scholarworks.rit.edu/theses/9734

6. Hamadi, Amer Mahdy. Autonomous Quadrotor Control Using Convolutional Neural Networks.

Degree: MS, Electrical Engineering, 2019, Rochester Institute of Technology

  Quadrotors are considered nowadays one of the fastest growing technologies. It is entering all fields of life making them a powerful tool to serve… (more)

Subjects/Keywords: None provided

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APA (6th Edition):

Hamadi, A. M. (2019). Autonomous Quadrotor Control Using Convolutional Neural Networks. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/9995

Chicago Manual of Style (16th Edition):

Hamadi, Amer Mahdy. “Autonomous Quadrotor Control Using Convolutional Neural Networks.” 2019. Masters Thesis, Rochester Institute of Technology. Accessed December 03, 2020. https://scholarworks.rit.edu/theses/9995.

MLA Handbook (7th Edition):

Hamadi, Amer Mahdy. “Autonomous Quadrotor Control Using Convolutional Neural Networks.” 2019. Web. 03 Dec 2020.

Vancouver:

Hamadi AM. Autonomous Quadrotor Control Using Convolutional Neural Networks. [Internet] [Masters thesis]. Rochester Institute of Technology; 2019. [cited 2020 Dec 03]. Available from: https://scholarworks.rit.edu/theses/9995.

Council of Science Editors:

Hamadi AM. Autonomous Quadrotor Control Using Convolutional Neural Networks. [Masters Thesis]. Rochester Institute of Technology; 2019. Available from: https://scholarworks.rit.edu/theses/9995

7. Sattar, Muhammad Awais. Adaptive Fuzzy Control of Quadrotor.

Degree: MS, 2017, Rochester Institute of Technology

  In this thesis, intelligent controllers are designed to control attitude for quadrotor UAV (Unmanned Aerial Vehicle).Quadrotors have a variety of applications in real time… (more)

Subjects/Keywords: Adaptive fuzzy PD; Dynamics; Fuzzy logic control; PD control; Roll pitch yaw; UAV

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Sattar, M. A. (2017). Adaptive Fuzzy Control of Quadrotor. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/9618

Chicago Manual of Style (16th Edition):

Sattar, Muhammad Awais. “Adaptive Fuzzy Control of Quadrotor.” 2017. Masters Thesis, Rochester Institute of Technology. Accessed December 03, 2020. https://scholarworks.rit.edu/theses/9618.

MLA Handbook (7th Edition):

Sattar, Muhammad Awais. “Adaptive Fuzzy Control of Quadrotor.” 2017. Web. 03 Dec 2020.

Vancouver:

Sattar MA. Adaptive Fuzzy Control of Quadrotor. [Internet] [Masters thesis]. Rochester Institute of Technology; 2017. [cited 2020 Dec 03]. Available from: https://scholarworks.rit.edu/theses/9618.

Council of Science Editors:

Sattar MA. Adaptive Fuzzy Control of Quadrotor. [Masters Thesis]. Rochester Institute of Technology; 2017. Available from: https://scholarworks.rit.edu/theses/9618

8. Baburajan, Silpa. Pitch Control of Wind Turbine through PID, Fuzzy and adaptive Fuzzy-PID controllers.

Degree: MS, Electrical Engineering, 2017, Rochester Institute of Technology

  As the penetration of the wind energy into the electrical power grid is extensively increased, the influence of the wind turbine systems on the… (more)

Subjects/Keywords: Adaptive fuzzy PID controller; Fuzzy controller; PID controller; Pitch angle; Wind energy

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Baburajan, S. (2017). Pitch Control of Wind Turbine through PID, Fuzzy and adaptive Fuzzy-PID controllers. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/9633

Chicago Manual of Style (16th Edition):

Baburajan, Silpa. “Pitch Control of Wind Turbine through PID, Fuzzy and adaptive Fuzzy-PID controllers.” 2017. Masters Thesis, Rochester Institute of Technology. Accessed December 03, 2020. https://scholarworks.rit.edu/theses/9633.

MLA Handbook (7th Edition):

Baburajan, Silpa. “Pitch Control of Wind Turbine through PID, Fuzzy and adaptive Fuzzy-PID controllers.” 2017. Web. 03 Dec 2020.

Vancouver:

Baburajan S. Pitch Control of Wind Turbine through PID, Fuzzy and adaptive Fuzzy-PID controllers. [Internet] [Masters thesis]. Rochester Institute of Technology; 2017. [cited 2020 Dec 03]. Available from: https://scholarworks.rit.edu/theses/9633.

Council of Science Editors:

Baburajan S. Pitch Control of Wind Turbine through PID, Fuzzy and adaptive Fuzzy-PID controllers. [Masters Thesis]. Rochester Institute of Technology; 2017. Available from: https://scholarworks.rit.edu/theses/9633

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