Research Interests

I'm interested in control and estimation theory for nonlinear and complex systems. In this regard, I'm particularly interested in the computer-controlled processes with high penetration of computing and communication technologies, including the so-called Cyber-Physical Systems (CPS). For those systems, I research control-theoretic methods for ensuring safety properties, such as stability, dissipativity, fault-tolerance, and trajectories containment, as well as the cyber-security properties whose concerns emerge from the intense use of novel communication technologies. Moreover, for dealing with nonlinear dynamics, I'm enthusiastic of methods based on differential inclusions (e.g., quasi-LPV and fuzzy models) which enable the use of optimization tools, e.g., semidefinite programming, for constructing the solutions. Some examples of problems related to this topic:

• Robust and nonlinear control and estimation;

• Fault-tolerant control;

• Dissipativity-based analisys and control;

• Networked control systems;

• Cyber-secure, resilient and non-fragile control.

The task of modelling real-world systems consists of developing methodologies that capture the dynamics of processes, which might be nonlinear and time-varying, and describing them with a certain precision. The control of those systems requires the characterization of the input-output relationships. Moreover, the data-driven supervision of those systems require methodologies with capabilities to process data-streams. In this regard, the evolving models play a crucial role on the autonomous artificial intelligence since they provide a fully adaptive behaviour in terms of model structure and parameters. Complementary, granular computing enables concept formation and learning to achieve explainable AI models. I'm interested in the combination of those approaches to develop evolving granular systems which allows to process data streams from complex and non-stationary sources, guaranteeing interpretability.

Prognostics and Health Management is used for assessment and prediction of state of degradation and remaining useful life (RUL) of structures, systems, and components as well as for the development of maintenance policies. I'm particularly interested in data-based methods for PHM and the development of predictive maintenance policies, which considers the RUL predictions for the planning of maintenance tasks, as well as the prescriptive maintenance and health-aware control methods that enable the design of controllers which are able to manage and extend the RUL of the equipments.