Full Form Dynamic Linearization based data-driven MFAC for a class of discrete-time nonlinear systems

In this paper, we propose a data-driven Model Free Adaptive Control (MFAC) scheme based on Full Form Dynamic Linearization (FFDL) for nonlinear systems. First, using FFDL technique, we transform a nonlinear system into an equivalent linear time-varying system with Pseudo-Partial Derivative vector as time-varying parameters. Second, we construct an indirect adaptive control system for the linear time-varying system. Finally, we analyze the stability and the tracking error of the MFAC scheme, show that all the signals in the closed-loop are bounded provided the parameter variations are small and present the dynamic equation of the tracking error.