The Systems and Control Group brings together more than 80 researchers whose work focuses on the modeling, analysis, optimization, estimation, and control of dynamical systems, with the ambition of addressing the scientific and technological challenges posed by the complex systems of the future.
Research within the Systems and Control Group spans both the theoretical and methodological foundations of systems and control as well as their practical applications. These activities are carried out through extensive collaborations with industrial partners and leading international research institutions.
Research topics
Nonlinear and hybrid approaches to control and dynamical systems (COMEDY team) Nonlinear systems and control; Switched and hybrid systems; Quantum systems
Interconnected dynamical systems: control and optimization (DISCO team) Time-delay systems; Convex optimization; Mean-field systems
Large-scale interconnected systems (MODESTY team) Partial differential equation (PDE) systems; Multi-agent systems; Observation and synchronization
Optimization and learning-based approaches to control and estimation (SYCOMORE team) Constrained control and estimation; Optimization and learning for systems and control
Fields of application
Energy and Environment
Autonomous Systems, Robotics, and Vehicles
Neuroscience and Healthcare
Life Sciences and Bioprocesses
Quantum Technologies
Artificial Intelligence
Teams of the Systems and Control Group
Modeling for the control of dynamical systems (COMEDY)
The COMEDY team focuses on the analysis of structural properties and the control of several classes of dynamical systems, including nonlinear, hybrid, quantum, and partial differential equation (PDE) systems. While the team’s research is primarily devoted to fundamental theoretical developments, it maintains strong connections with practical applications. These include neurophysiological systems analysis, active vibration control, real-time scheduling, networked control systems, and quantum control.
Interconnected dynamical systems: control and optimization (DISCO)
Adopting a model-based approach, the DISCO team develops (optimal) control methods for interconnected systems, including large-scale systems. Its ultimate goal is to produce computationally efficient and practically implementable solutions, with a particular emphasis on low-complexity controllers that can be readily deployed in real-world applications.
Modeling, estimation, and analysis of dynamical systems (MODESTY)
The MODESTY team investigates large-scale interconnected systems. These systems are considered large-scale either because they consist of a large number of interacting subsystems, such as multi-agent systems or interconnected nonlinear systems, or because they are governed by infinite-dimensional dynamics, including partial differential equations (PDEs) and time-delay systems, which may themselves be interconnected through communication or physical networks.
Robust and constrained control of complex systems (SYCOMORE)
The SYCOMORE team’s methodological research spans a broad spectrum of theoretical approaches, ranging from modeling and estimation—particularly robust estimation—to the constrained control of uncertain complex systems, as well as fault diagnosis and fault-tolerant control. The control strategies developed by the team—including predictive, robust, and nonlinear control methods—rely on optimization techniques based on tailored heuristics. Current research also emphasizes distributed and decentralized control architectures designed to address the challenges posed by cyber-physical systems.
