LMI-Driven Tracking Control of Fuzzy Nonlinear Cyber-Physical Systems: Application to Quadrotor UAVs in Urban-Like Environment

This paper aims to present a tracking control framework for nonlinear cyber-physical systems (CPSs), formulated via linear matrix inequalities (LMIs) and fuzzy modeling approach. In general, CPSs are sophisticated systems in which cyber components (e.g., digital controllers and communication modules) are tightly integrated with physical components (e.g., actuators and sensors). Such a tight integration often introduces significant system nonlinearities into the overall dynamics, making the control and coordination of CPSs particularly challenging. The key advantage of the proposed fuzzy model-based approach is that it allows us to represent nonlinear system dynamics as a convex combination of linear subsystems weighted by their corresponding membership functions. This formulation allows well-established linear control and system-theoretic methods to be effectively applied to nonlinear CPSs. Finally, the effectiveness of the proposed LMI-based framework is demonstrated through a case study on quadrotor unmanned aerial vehicles (UAVs) performing tracking control in urban-like environments.