TABLF-based adaptive control for uncertain nonlinear systems with time-varying asymmetric full-state constraints

In this paper, we investigate the tracking control problem for a class of strict-feedback nonlinear systems with parametric uncertainties and time-varying asymmetric full-state constraints. By introducing novel tan-type time-varying asymmetric barrier Lyapunov function (TABLF) in each step of backstepping design, the boundedness of the fictitious state tracking errors are ensured. A novel adaptive backstepping control design based on tuning function is given, which successfully eliminates the effect of uncertainties. In addition, only one parameter needs to be adjusted online in the control design, which greatly alleviates the computation burden. Based on the proposed control scheme the asymptotic convergence of system output tracking error is realised and the time-varying full-state constraints are not violated for all the time. A numerical example is given to illustrate the effectiveness of the proposed control scheme.

Automated summary

This paper presents a novel control design approach to address the tracking control problem of nonlinear systems with parametric uncertainties and constraints, achieving system stability and satisfaction of full-state constraints.