Nonlinear fractional order data driven controller design for nonlinear systems - دانشکده فنی و مهندسی
Nonlinear fractional order data driven controller design for nonlinear systems
نوع: Type: رساله
مقطع: Segment: دکتری
عنوان: Title: Nonlinear fractional order data driven controller design for nonlinear systems
ارائه دهنده: Provider: Amir Veisi
اساتید راهنما: Supervisors: Dr. Hadi delavari
اساتید مشاور: Advisory Professors:
اساتید ممتحن یا داور: Examining professors or referees: Dr. Mohammad Hasan Moradi, Dr. Seyyed Sajjad Moosapour, Dr. Seyed Mohammad Azimi
زمان و تاریخ ارائه: Time and date of presentation: 2025
مکان ارائه: Place of presentation: 33
چکیده: Abstract: Due to the problems associated with fossil fuels, including environmental pollution and the gradual depletion of these resources, increasing attention has been directed toward generating energy from clean and renewable sources such as solar, wind, and geothermal energy. Among these, wind energy has been selected for investigation in this thesis because of its vast potential and numerous advantages. One of the main challenges in this area is extracting the maximum possible output power from these renewable and clean energy sources. Therefore, various control strategies have been developed to achieve maximum power generation. In addition to maximizing power output, another critical challenge is ensuring system robustness against factors such as disturbances, parameter uncertainties, and other nonlinear effects. In this thesis, several robust fractional-order nonlinear controllers are designed for the rotor-side converter of a doubly-fed induction generator (DFIG). The proposed controllers are developed by integrating fractional calculus, sliding mode control, and backstepping techniques. Sliding mode observers and radial basis function (RBF) neural networks are employed to estimate the external disturbances affecting the system. The closed-loop stability of the proposed control systems is analytically proven using the generalized Lyapunov theory. Finally, the performance of the proposed methods is evaluated and compared with other existing approaches under specific operating conditions.