Hybrid Systems Theory

In theory, our group studies modeling, analysis and control of the stochastic hybrid system (SHS) which is a dynamical system with the interacting discrete dynamics (represents the logical/cyber behavior) and continuous dynamics (describes the physical behavior) of the CPS with uncertainties, and thus it can accurately model the CPS.

Our group develops a set of SHS models and corresponding hybrid estimation and control theory and algorithms which can deal with a range of SHS computationally efficiently, and thus can be applied to various complex CPS applications.

• Hybrid Systems Modeling
• Hybrid Estimation
• Optimal Control of Hybrid Systems

We further extend our hybrid systems research to a wide range of problems such as

• Event-based state estimation for SHS (e.g., sensor/vehicle network);
• Optimal state estimation and control for partially observable SHS (e.g., UAS control algorithm);
• Robust state estimation for SHS; and
• Fault detection and identification for state constrained SHS (e.g., cybersecurity of UAS).