ADP-based fixed-time prescribed performance attitude control with partial-state feedback

In this paper, the partial-state feedback near-optimal prescribed performance attitude tracking control problem is studied. To address engineering challenges, we consider unmeasurable angular velocity, external disturbances, actuator faults, and employ an event-triggered mechanism to reduce the computational burden. First, a novel fixed-time prescribed performance function (FtPPF) is designed to guarantee that the relative attitude converges within a user-defined time, ensuring both transient and steady-state performance of the system. Transforming the constrained system to the unconstrained one, an extended state observer (ESO) is developed to reconstruct the unmeasurable angular velocity and estimate the lumped uncertainty due to external disturbances, actuator faults, and the event-triggered mechanism. Furthermore, an adaptive dynamic programming (ADP)-based framework is proposed for the partial-state feedback near-optimal FtPPF-ADP control policy, thereby guaranteeing performance constraints while minimizing real-time control cost. Then, Lyapunov stability analysis confirms the uniform ultimate boundedness of the closed-loop system states. Finally, numerical simulations validate the effectiveness of the proposed control scheme.