Control Theory is closely related to (and can be applied in) a broad range of disciplines. Consequently, the systems to be controlled include non-physical things (e.g., the opinion of a population on a specific topic) and physical systems (e.g., a power converter). 

My research interests focus on physical systems, including, but not limited to, robots, electromechanical systems, and electrical systems. Lately, I have been particularly interested in model-based control for soft robots.

The behavior of physical systems is ruled by how they store, dissipate, and route energy. Accordingly, modeling physical systems based on these concepts is natural and intuitive. Examples of these modeling approaches are the Euler-Lagrange formalism and the port-Hamiltonian framework. Following this same rationale, some nonlinear control techniques (e.g., passivity-based control) focus on energy and dissipation, endowing the resulting controllers with a physical interpretation.

Models with "large" dimensions might be challenging to handle, making them impractical for simulation and control purposes. Model reduction techniques offer solutions to this problem by proposing reduced-order models that are easier to manipulate.

In many applications, guaranteeing stability is not enough. Most of the time, ensuring a desired performance for the closed-loop system is necessary. Other common implementation issues are actuators' dead zones and saturation. An important part of my research focuses on addressing such issues.