Dear NU Community!
NU's PhD Program in Robotics Engineering is delighted to invite you to the PhD Thesis Defense:
Candidate: Darkhan Zholtayev, 4th year PhD student.
Thesis Title: Model-free control design for permanent magnet synchronous generator in wind energy conversion systems.
Lead Supervisor: Prof. Ton Duc Do, Dept. of Robotics Engineering, School of Engineering and Digital Sciences, NU, Kazakhstan.
Co-Supervisor: Dr.Matteo Rubagotti, School of Engineering and Digital Sciences, NU, Kazakhstan.
External Co-Supervisors: Prof. Nguyen Gia Minh Thao,Graduate School of Engineering, Toyota Technological Institute.
Chair-Internal Examiner: Prof. Michele Folgheraiter, Dept. of Robotics Engineering, School of Engineering and Digital Sciences, NU, Kazakhstan.
Internal Examiner: Prof. Zhanat Kappassov, Assistant Professor, Dept. of Robotics Engineering, School of Engineering and Digital Sciences, NU, Kazakhstan.
External Examiner: Prof. Binh-Minh Nguyen, The University of Tokyo, Japan.
Lead supervisor Examiner: Prof. Ton Duc Do, Dept. of Robotics Engineering, School of Engineering and Digital Sciences, NU, Kazakhstan.
Abstract:
This research investigates advanced control methods for electric engines, with a focus on Wind Energy Conversion Systems (WECS), in pursuit of sustainable and efficient energy solutions. Electric machines permeate many facets of our daily lives, ranging from household appliances to industrial applications, making their efficient management a necessity. WECS, which are characterized by inherent nonlinearity, present challenges that necessitate sophisticated control strategies for efficient power harvesting, assuring power quality, and minimizing system wear and tear.
The investigation of an advanced model-based control method, Super-Twisting Adaptive Sliding Mode Control (ST-ASMC), for Permanent Magnet Synchronous Generator (PMSG)-based WECS is the focus of this research. ST-ASMC is presented as an effective solution, preserving the robustness characteristics of conventional sliding mode control while reducing chattering via gain adaptation and the generation of second- order sliding modes. ST-ASMC facilitates optimal power acquisition by resolving a nonlinear multi-input multi-output tracking control issue. The proposed control method outperforms other sliding mode control techniques in the presence of variations in stator resistance, stator inductance, and magnetic flux linkage, as determined by comparative simulation studies employing actual wind speed data.
Date and time: November 24, 2023 (Friday) at 19:00, Astana time.
The defense will be held Offline at 3e220 and via Microsoft Teams platform. Please make sure that you have installed it on your computers/devices.
Join Microsoft Teams Meeting:
https://teams.microsoft.com/l/meetup-join/19%3ameeting_YjQ5NjI5MmMtZmQ3Zi00MmIxLTkwZDMtYTkyYTYzOTczMWQw%40thread.v2/0?context=%7b%22Tid%22%3a%2221fe413c-53ab-42a9-8f23-64725363c212%22%2c%22Oid%22%3a%22b5bb6721-b80a-4448-9756-0a1955821c04%22%7d
Contact information: SEDS Academic and Student Affairs Office Phone: +7 (7172) 70-64-23, 70-64-82
