Asymptotic stabilization of feedback linearizable systems via estimated diffeomorphism

Abstract

The traditional feedback linearization method often requires the full system parameter and state information. In this paper, we consider an asymptotic stabilization problem of a class of feedback linearizable nonlinear systems by using less than the full parameter/state information. First, our approach is to classify system parameters into two categories -'directly used parameters' and 'indirectly used parameters.' Then, a feedback linearizing controller is designed by using only the 'directly used parameters' and the observer is utilized to estimate the transformed states (diffeomorphism) which includes 'indirectly used parameters.' Thus, in our control approach, we use only a partial set of system parameters and partial state information for asymptotic stability. The useful aspects of the proposed scheme are illustrated through an example.