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In this paper, an indirect adaptive neuro fuzzy controller is proposed for controlling nonlinear affine systems, inspired by the theory of feedback linearization and adaptive network-based fuzzy inference system (ANFIS). In a nonlinear affine system two ANFIS are used to model nonlinear dynamic functions of the plant. The adaptive fuzzy rules are applied, such that the feedback linearization control input can be best approximated and the closed-loop system is stable. Simulation results indicate the remarkable capabilities of the proposed control algorithm and good transient response characteristics of the output system.