Asymptotic Stability Control With Full-State Constraints for Nonlinear MIMO Systems and Its Application to Aircraft

In this article, we propose a full-state constraints asymptotic stability control for nonlinear multiple-input-multiple-output (MIMO) systems. This algorithm addresses the full-state constraints problem by restricting the constraint intervals to only the system states, thus compensating for the limitations of barrier Lyapunov functions. Additionally, it ensures the asymptotic stability of the closed-loop system in the presence of unknown functions. In contrast to neural network and fuzzy approximation algorithms, our proposed algorithm facilitates the convergence of system states to the origin without relying on assumptions about unknown functions. This leads to a reduction in conservatism compared to these algorithms. Furthermore, a simulation example is provided to demonstrate the effectiveness and superiority of the proposed algorithm.