In this work, a novel higher-order model-free adaptive control scheme is presented based on a dynamic linearization approach for a class of discrete-time single input and single output (SISO) nonlinear systems. The control scheme consists of an adaptive control law, a parameter estimation law, and a reset mechanism. The design and analysis of the proposed control approach depends merely on the measured input and output data of the controlled plant. The control performance is improved by using more information of control input and output error measured from previous sampling time instants. Rigorous mathematical analysis is developed to show the bounded input and bounded output (BIBO) stability of the closed-loop system. Two simulation comparisons show the effectiveness of the proposed control scheme.

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