Advanced & Robust Control Systems

We design control architectures that keep industrial processes stable and efficient under uncertainty, delay, and disturbance. Our work covers robust and H∞ control, networked cascade control systems, fuzzy and neuro-fuzzy feedback-feedforward schemes, and model-based/model-free control of servo-pneumatic and combustion systems — applied to steam power plants, fired-heater furnaces, and gas turbines. Recent work extends classical control theory with optimization and soft-computing techniques (genetic algorithms, Takagi–Sugeno fuzzy inference) to handle nonlinear dynamics and network-induced imperfections, published in the International Journal of Control and IEEE Transactions on Automation Science and Engineering.