Data-driven model free adaptive control for a class of interconnected systems

This paper recalls a novel data-driven model-free adaptive control (MFAC) method for a class of interconnected discrete-time nonlinear systems, whose model is unavailable and interactions between each subsystem are measurable. Then, under some mild conditions, stability of the closed-loop system is analyzed theoretically. Compared with original MFAC, the proposed MFAC for interconnected systems belongs to decentralized control method, and makes full use of the interacted data to achieve better performance. The effectiveness and superiority are verified by simulation result.