This course introduces the foundations of modern control theory for multivariable dynamic systems, providing the tools needed to analyze, design, and reason about complex systems in both continuous and discrete time. Starting from state-space modeling and Linear Time-Invariant (LTI) systems, the course develops a rigorous framework for understanding stability, structural properties, feedback, robustness, and optimization-based control.
The theory is tightly connected to real-world applications, including robotics, autonomous systems, aerospace, power and energy systems, process control, and cyber-physical systems. Through lectures and hands-on laboratory sessions using Matlab/Simulink, students learn how abstract concepts such as controllability, observability, state feedback, observers, and robustness translate into practical control architectures for real engineering systems.
By the end of the course, students will be equipped to analyze dynamic behavior, design feedback controllers, and make informed design choices under uncertainty, with a solid theoretical background aligned with current engineering practice and societal challenges, including those addressed by the UN 2030 Sustainable Development Goals.
The theory is tightly connected to real-world applications, including robotics, autonomous systems, aerospace, power and energy systems, process control, and cyber-physical systems. Through lectures and hands-on laboratory sessions using Matlab/Simulink, students learn how abstract concepts such as controllability, observability, state feedback, observers, and robustness translate into practical control architectures for real engineering systems.
By the end of the course, students will be equipped to analyze dynamic behavior, design feedback controllers, and make informed design choices under uncertainty, with a solid theoretical background aligned with current engineering practice and societal challenges, including those addressed by the UN 2030 Sustainable Development Goals.
- Teacher: FELICE ANDREA PELLEGRINO