Adaptive control of linearizable discrete-time systems

Abstract

The adaptive control of feedback linearizable discrete-time systems is studied. The nonlinearities in the system are linear combinations of known nonlinear functions. Although the unknown parameters appear linearly, the convergence result obtained is not global. The maximum allowable parameter error depends on the system characteristics and on the initial system states. Simulations show that the system diverges when the initial parameter error is too large.