ADAPTIVE CONTROLLER DESIGN FOR NONLINEAR SYSTEMS UNDER STATE CONSTRAINTS USING BARRIER LYAPUNOV FUNCTIONS AND INTEGRATOR BACKSTEPPING
DOI:
https://doi.org/10.60787/jnamp.vol73no.753Keywords:
Adaptive-Control, Barrier Lyapunov, Functions, Integrator, Backstepping, Nonlinear Systems, State ConstraintsAbstract
In this work, we develop a robust adaptive control framework for a class of uncertain nonlinear systems in strict-feedback form, incorporating explicit state constraints. By combining integrator backstepping methodology with
logarithmic Barrier Lyapunov Functions (BLFs), the proposed controller guarantees asymptotic tracking and stabilization while strictly preventing system states from violating predefined safety boundaries. Parameter
uncertainties are handled via adaptive update laws designed to ensure global uniform boundedness of all closed-loop signals. Stability analysis was conducted using Lyapunov stability theory and Barbalat’s lemma. Numerical simulations for a three-state nonlinear system validate the theoretical findings, demonstrating effective open-loop instability mitigation, precise constraint enforcement, and robust trajectory tracking of reference signals.
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