Abstract: Due to the increasing level of autonomy and rapid technological advancements in sensing, computing, and communication, nowadays, many real-world applications are expected to do complex tasks. These complex tasks can be formally represented using spatio-temporal logic specifications or (in)finite strings over automata. On the other hand, the modelling complexities in real-world applications, such as combination/interconnection of physical and cyber components, noisy dynamics, dependency on state history, lack of knowledge of the exact mathematical model, interconnection between subsystems, constraints posed by implementing hardware platforms, are increasing. These system- and task-level complexities make the formally correct synthesis of control algorithms challenging. Solving this problem is beyond the scope of conventional control theory and needs to utilize some concepts from computer science.
In this talk, I will discuss my research contributions on combining knowledge from different theories of control systems, computer science and AI/ML to synthesize formally verified controllers for complex control systems (i.e., containing the aforementioned modelling complexities) that ensure the satisfaction of complex logical specifications.
