Abstract
A new adaptation mechanism is proposed for the tuning functions based adaptive backstepping control for a class of nonlinear systems. The new scheme combines direct and indirect parameter update regimes in an effort to improve the speed and accuracy of the adaptation which in turn leads to increased tracking performance. The parameter update dynamics is driven both by the identification error and the tracking error defined in the backstepping control. The closed loop error dynamics is shown to be globally stable by using a recursive mechanism based on Lyapunov analysis with tracking error convergence along with identification error convergence. The proposed scheme is tested on two benchmark examples in order to demonstrate its performance increase compared to the tuning functions based adaptive backstepping scheme.
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