Abstarct: Ideal feedback linearization is defined for the case when the system parameters are known. Adaptive feedback linearization is employed to get asymptotically exact cancellation for the inherent uncertainty in the knowledge of the given system parameters. The control algorithm is implemented using the feedback linearization technique and adaptive method. The controller parameters are unknown and an adaptive law that aims to drive them towards their ideal values that would provide perfect model matching between the reference model and the closed-loop plant model. The converged controller parameters would then provide good estimates for the unknown plant parameters. This approach allows the feedback linearization technique to be used in an adaptive way. The results are confirmed both analytically and by simulation.