Adaptive Asymptotic Tracking Control of Strict-Feedback Nonlinear Parameterized Systems

In this paper, an adaptive control tactic is designed for a class of nonlinear systems with nonconvex parameterization by using the backstepping method. During the backstepping control process, an improved nonlinear filter with a compensation term is introduced to deal with the repetitive differentiation problem of the designed virtual controllers, which removes the boundary layer error simultaneously. The nonconvex pa-rameterized terms are discussed in light of the extensions of explicit realizability assumptions. Under the constructed control algorithms, the bound ness of all signals in the closed-loop system is proved, and the tracking error can reach 0 as time approaches to infinity. Finally, the effectiveness of the proposed method is demonstrated through a simulation example.