Adaptive tracking control for nonlinear input-delay systems with full state constraints and unmodeled dynamics

An innovative adaptive tracking control strategy is proposed in this paper for a class of nonlinear systems, which considers input-delay, full state constraints, and unmodeled dynamics simultaneously. To address the system’s unknown nonlinear dynamics, the approximation ability of multi-dimensional Taylor network (MTN) is employed in the controller design process. The effect of input-delay is reduced through the application of Pade approximation. Additionally, the impact of state constraints is mitigated through the introduction of barrier Lyapunov functions (BLFs). To deal with unmodeled dynamics, a dynamic signal is formulated. By integrating the backstepping control strategy with Lyapunov stability theory, it is ensured that all signals in the closed-loop system remain bounded, the tracking error approaches a small region close to the origin, and the full state constraints are not violated. Finally, simulation results are provided to validate the proposed strategy’s effectiveness.