Control System Theory is a mature discipline. Surprisingly, however, the existing methodologies tend to be limited to relative standard problems such as linear, unconstrained and centralized architectures. As soon as one departs from these settings one is soon faced with severe difficulties.
Unfortunately, many real-world problems fall into these, so-called, “complex” problems. These problems include such features as nonlinear and non-smooth behavior, high state dimension and lack of convexity. Control System Theory Research Lab is aimed at addressing these issues using alternative theoretical tools such as Robust Control, Nonlinear Control, Intelligent and Fuzzy Control, Fault-Tolerant Systems, Optimal Control, Neural Networks, and MPC.
