جستجوی استاد راهنمای دانشگاهی

Anders Rantzerمشاهده پروفایل

استاد

• Control Systems Theory
• Scalable Control
• Adaptive Control
• +۷ مورد دیگر

Anders Rantzer is a Professor of Automatic Control at the Department of Control Engineering, Faculty of Engineering, Lund University, Sweden. He has held visiting positions at Caltech (2004–2005) and the University of Minnesota (2015–2016) as the Taylor Family Distinguished Visiting Professor. His academic journey began with a PhD from KTH Stockholm in 1991, followed by a postdoc at the Institute for Mathematics and its Applications (IMA), University of Minnesota. His research interests center on modeling, analysis, and synthesis of control systems , with a strong focus on scalability, adaptation, and applications in energy networks . He is particularly known for foundational work in positive systems and integral quadratic constraints (IQCs) . These theoretical frameworks are critical in analyzing stability and robustness of large-scale interconnected systems. His work bridges mathematical rigor with practical engineering applications, especially in sustainable energy and networked systems. The recent publications and lecture materials reflect a consistent trajectory in scalable and robust control, optimization, and distributed systems. Themes such as large-scale convex optimization , nonlinear and stochastic control , and network dynamics dominate his scholarly output, indicating a sustained commitment to advancing control theory for complex, real-world systems. Scientific honors include: Fellow of IEEE Member of the Royal Swedish Academy of Engineering Sciences (IVA) Chairman of the Swedish Scientific Council for Natural and Engineering Sciences Chairman of the Royal Physiographic Society of Lund Rantzer has supervised numerous students and contributed extensively to academic leadership and education. He has been involved in major national and international research initiatives such as WASP (Wallenberg AI, Autonomous Systems and Software Program) and ELLIIT. His work includes developing educational tools and courses in control, optimization, and machine learning. He leads and contributes to research projects on autonomous systems, cloud control, and smart energy networks. He is affiliated with the Control Lab at LTH and participates in collaborative efforts such as the Nordic University Hub on Industrial Internet of Things (HI2OT). His work integrates theoretical advances with practical implementations in robotics, biomedical systems, and industrial automation.

• Fluid Power Engineering
• Hydraulic Systems
• Tribology
• +۴ مورد دیگر

Prof. Dr.-Ing. Katharina Schmitz serves as Institute Director and Vice Dean at the Institute for Fluid Power Drives and Systems, RWTH Aachen University. Her leadership within the Production Technology Cluster and extensive contributions to fluid power engineering establish her as a leading authority in mechanical engineering research and education. Her research spans fluid power systems, hydraulic component design, tribology, and physics-informed machine learning applications. She pioneers sustainable propulsion solutions through bio-hybrid fuels research while addressing fundamental challenges in polymer material behavior under hydraulic stresses. Current work focuses on carbon-neutral heavy-duty transportation, physics-based neural networks for lubrication modeling, and advanced control systems for electro-hydraulic actuators. Analysis of her 15 most recent publications reveals a dominant trend toward integrating physics-based modeling with deep learning to solve complex engineering problems. Her team consistently develops novel frameworks for cavitation prediction, flow rate determination, and material compatibility assessment - significantly advancing fluid power system reliability, efficiency, and digitalization. Scientific recognition includes: GfT Förderpreis 2023 for experimental and simulative investigation of partially hydrostatic relieved contacts in variable speed axial piston machines As head of the Institute for Fluid Power Drives and Systems, she leads cutting-edge research in sustainable fluid power technologies. The institute maintains strong industry partnerships while driving innovation in hydraulic component design, digital twins for condition monitoring, and next-generation propulsion systems through its position within RWTH Aachen's Production Technology Cluster.

• Epidemics
• Social Network
• Neural network control
• +۳ مورد دیگر

Yuhong Chen is a Ph.D. candidate at the Chair of Control Engineering (Prof. Buss) at the Technical University of Munich . She holds a Master of Engineering in Control Science and Engineering from Harbin Institute of Technology (2017-2019) and a BSc in Automation from the same university (2013-2017). Research Focus: Neural network control, reinforcement learning, epidemics modeling, and social network analysis Expertise: 3-DOF helicopter control systems, electro-hydraulic servo systems, time-delay compensation Recent publications demonstrate expertise in adaptive control algorithms, machine learning applications in robotics, and nonlinear system stabilization. She has contributed to IEEE/ASME Transactions and conference proceedings. Contact: Email yuhong.chen@tum.de for thesis supervision opportunities or student projects in control systems research.

• Backstepping Control
• Optimal Control
• Robotics
• +۳ مورد دیگر

Yongchao Wang is a Professor in the Department of Automatic Control Engineering at Technische Universität München (TUM). He has an extensive academic background, including a Ph.D. from TUM (2019-2022) and Xidian University (2016-2018), an M.Sc. (2013-2016), and a B.Sc. (2009-2013), all in Control Science and Engineering. B.Sc., Control Science and Engineering, Xidian University (2013) M.Sc., Control Science and Engineering, Xidian University (2016) Ph.D., Control Science and Engineering, Technische Universität München (2022) & Xidian University (2018) His research focuses on Backstepping Control , Optimal Control , and Robotics , particularly in developing robust control strategies for high-dimensional robotic systems. Recent work includes advancements in Reinforcement Learning , Model Predictive Control (MPC) , and Adaptive Control for robotic tracking and stability. Key publication trends include: Application of Reinforcement Learning to robotic control optimization Development of robust and singularity-free MPC techniques Innovations in adaptive and sliding mode control for uncertain systems Time-delay estimation and concurrent learning approaches for stability Currently, no scientific awards or explicit student advising records are documented in available sources.

Abdurrahman Irscheidمشاهده پروفایل

پژوهشگر

• Control Theory
• Partial Differential Equations (PDEs)
• Nonlinear Control Systems
• +۷ مورد دیگر

Dr. Abdurrahman Irscheid is a Researcher at the Chair of Systems Theory and Control Engineering under Prof. Rudolph at Saarland University. He holds a Doctorate (Dr.-Ing.) from the university and has been a research assistant since 2018, with prior student assistant roles dating to 2013. His research focuses on control and observer design for hyperbolic/parabolic PDEs, finite-time convergence methods, and cooperative load transportation with heavy ropes. He has supervised over a dozen theses and projects, including experimental validations of control systems. Educational Background: B.Sc. Mechatronics, Saarland University (2012-2015) M.Sc. Computational Engineering of Technical Systems (COMET), Saarland University (2015-2017, with distinction) Doctorate (Dr.-Ing.), Saarland University (2025) Research Interests: Boundary control of distributed-parameter systems Observer and backstepping design for hyperbolic PDEs Prescribed-time stabilization of nonlinear systems Flatness-based control for complex mechanical systems Applications in load transportation and dielectric elastomer actuators Awards: Best Paper Award (at-Automatisierungstechnik 2023) VDI-Preis 2019 (outstanding Master's thesis) VDE-Saar Preis (top electrical engineering graduation) Stiftungspreis 2018 (top Master's thesis) Teaching & Supervision: Lead exercises in Systems Theory and Control Engineering courses since 2018 Supervised 11+ theses/projects (e.g., observer-based controllers for heavy rope systems, prescribed-time stabilization) Co-advised projects on rotational pendulums and mobile platforms Labs/Teams: Active in the LSR research group focusing on distributed-parameter systems and nonlinear control applications.

Johannes Reuterمشاهده پروفایل

استاد

• Control Engineering
• Autonomous Systems
• Maritime Control
• +۳ مورد دیگر

Prof. Johannes Reuter is a Professor in the Department of Control Engineering at Konstanz University of Applied Sciences and a member of the Institute for System Dynamics (ISD). He serves as Vice Dean and Dean of Studies for the Electrical Systems M.Eng. program. His expertise includes control engineering, tracking, and multi-sensor data fusion. Reuter holds a doctorate in Automatic Control and System Dynamics from Berlin Technical University. Before joining Konstanz in 2007, he worked at IAV GmbH, IAV Automotive Engineering (USA), and Eaton Corp.'s Innovation Center (USA). His research focuses on autonomous systems, maritime control, and optimization algorithms, with contributions to conferences like ICRA and journals such as the Journal of Ocean Engineering. He leads projects on energy-efficient autonomous vessels (Solgenia) and advanced control strategies for dynamic systems. Education: Studied Mathematics/Physics at Bielefeld University Electrical Engineering degrees from Bielefeld University of Applied Sciences and Berlin Technical University Doctorate in Automatic Control and System Dynamics, Berlin Technical University Research Interests: Reuter’s work bridges theoretical control engineering with practical applications, emphasizing autonomous systems, maritime robotics, and sensor data fusion. Key areas include model predictive control (MPC), trajectory optimization, and energy-efficient vessel design. His research often integrates advanced algorithms like MPPI (Model Predictive Path Integral) for stochastic systems and develops methods for extended object tracking using LiDAR and radar sensors. Publications: Recent work highlights energy-optimal vessel docking, trajectory planning with signal temporal logic, and extended object tracking. His articles reflect a focus on interdisciplinary solutions combining control theory, robotics, and sensor technology. Awards/Grants: No specific awards listed, but his work is supported through academic and industrial collaborations. Labs/Teams: Active in the Institute for System Dynamics (ISD), Konstanz, which focuses on control systems, signal processing, and dynamic optimization across robotics, marine systems, and energy management.

• Robotics
• Human-Robot Interaction
• Autonomous Systems
• +۳ مورد دیگر

Dirk Wollherr is a Senior Researcher and Lecturer (Privatdozent) at the Institute of Automatic Control Engineering, Faculty of Electrical Engineering and Information Technology, Technical University of Munich (TUM). He received his Dipl.-Ing. (2000), Dr.-Ing. (2005), and Habilitation (2013) from TUM. His career includes research at TU Berlin and a JSPS Fellowship at the University of Tokyo. He led the Cluster of Excellence 'Cognition for Technical Systems' (2006-2008) and is a TUM Carl-von-Linde Junior Fellow (2010-2013). Research Interests: Autonomous mobile robots, human-robot interaction, SLAM, real-time trajectory planning, stochastic model predictive control, and robotic manipulation under uncertainty. His work bridges control theory and practical applications in urban robotics, agriculture automation, and autonomous vehicles. Publication Trends: Recent articles (2021-2025) focus on robust control under uncertainty, human-robot collaboration, agricultural automation, and probabilistic motion planning. Key themes include constraint violation minimization, data-driven control, and ethical human-robot interaction. Awards & Recognition: Japanese Society for the Promotion of Science (JSPS) Research Fellowship (2004) TUM Carl-von-Linde Junior Fellowship (2010-2013) Projects & Leadership: Principal investigator in EU projects (Robot@CWE, IURO), General Chair of Robotik 2008, and Co-Chair of ARSO 2013. Leads research on the Autonomous City Explorer and human-robot interaction frameworks.

• Control Systems
• Fault Detection and Diagnosis
• Distributed-Parameter Systems
• +۳ مورد دیگر

Professor Fischer is a researcher specializing in control systems and fault diagnosis, focusing on distributed-parameter systems, integral transformations, and trajectory planning methods. His work bridges theoretical advancements with practical applications in engineering disciplines. He has supervised numerous PhD graduates, including Johannes Pfeiffer (2023), Carmen Sippel (2023), Zaid Dhannoon (2022), and others, many of whom entered academia or industry roles post-graduation. Research Interests: Fault detection in hyperbolic/parabolic systems, modulating functions, backstepping control, and MATLAB toolbox development for control problems. Recent Trends: Emphasis on algebraic methods for fault diagnosis, with contributions to structural health monitoring (e.g., Euler-Bernoulli beam analysis) and time-varying hyperbolic systems. His publications since 2016 highlight advancements in fault detection for parabolic and distributed systems, with a 2021 paper introducing the coni MATLAB toolbox for control problem solutions. Advising: 8 PhD graduates listed, with graduation dates ranging from 2016 to 2023. Notable first employments include academic and industrial R&D positions.

• Control Engineering
• Distributed Parameter Systems
• Renewable Energy Integration
• +۵ مورد دیگر

Prof. George Weiss is a Professor of Control Engineering at the The Iby and Aladar Fleischman Faculty of Engineering , Tel Aviv University . His research focuses on Distributed Parameter Systems , Passive and Conservative Systems , and Control in Power Electronics , with applications to Renewable Energy Integration and Power Grid Stability . He leads the Power Electronics for Renewable Energy Lab and co-developed the synchronverter technology for renewable grid integration. Education : PhD in Applied Mathematics, Weizmann Institute (1989); MEng in Control & Computer Engineering, Polytechnic Institute of Bucharest (1981). His research interests span control theory (repetitive control, internal model principle), power electronics (converters, inverters), and renewable energy systems (wind turbines, wave energy). Recent work addresses grid stability with virtual synchronous machines , virtual infinite capacitors , and nonlinear damping in power systems . His students include Prof. Qing-Chang Zhong (Illinois Tech), Prof. Bayu Jayawardhana (Groningen), and researchers in power electronics and control across UK, China, and Israel. Grants include the ConFlex European Training Network (4M Euro, 2017-2021), ISF and EPSRC projects on wind turbine vibration suppression and wave energy prediction. He serves as Associate Editor for journals like Automatica and IEEE Control Systems Letters . Scientific Awards : Chercheur d'Excellence grant (France, 2013) He advises on renewable energy systems through consulting roles at MST Solar , Coriolis Wind , and SolarEdge , and co-founded Synvertec for synchronverter technology.