This paper addresses the problem of adaptive fixed-time attitude stabilization for uncertain rigid spacecraft with inertia uncertainties, external disturbances, actuator saturations, and faults. A nonsingular fixed-time sliding mode surface is constructed so that the settling time of the established surface is independent of the system initial states. By employing an exponential function in the controller design, an adaptive fixed-time control scheme is proposed to shorten the time during which the system states reach the sliding mode surface. With the proposed control method, the information on the bound of the lumped uncertainty is not needed in prior but estimated by the designed update laws. The fixed-time convergence of both the attitude and angular velocity is established, and comparative simulations are presented to illustrate the effectiveness of the proposed control scheme.

This article proposes a novel adaptive nonsingular predefined-time control strategy for rigid spacecrafts with inertia uncertainties. Following the backstepping recursive design procedures, an adaptive attitude controller is systematically presented to ensure that the spacecraft attitude can converge into a small region around the origin within a predefined time, which can be explicitly determined in advance by assigning a simple parameter. Moreover, by designing quadratic functions in the controllers, the singularity can be avoided directly without using any filters or piecewise continuous functions, such that the stability analysis becomes more concise and straightforward. Simulations are conducted to show the effectiveness of the presented method.

Most of the existing control methods for servo systems driven by hydraulic actuators have been developed by using backstepping scheme and assuming that all system states (including internal hydraulic signals) are measurable. In this paper, we propose a new control design method for high-order servo systems with hydraulic actuator dynamics, where the backstepping scheme is avoided and only the system output (e.g., motion displacement) is required for the control implementation. For this purpose, the system model is first transformed into a canonical form, where the unknown dynamics in the system are lumped as one term. Then, we introduce a simple robust unknown dynamics estimator (UDE) that has only one tuning parameter but achieves exponential error convergence to accommodate the lumped uncertainties. Therefore, the function approximators (e.g., neural network and fuzzy systems) can be avoided, leading to reduced computational costs, simpler parameter tuning and improved convergence as compared to backstepping methods. Extensive simulations and experiments based on a realistic test-rig are conducted to show the efficacy of the proposed control.

This study focuses on the adaptive fuzzy predefined-time attitude tracking control problem for rigid spacecraft with inertia uncertainties, external disturbances, and state constraints. In control design, fuzzy logic systems (FLSs) are adopted to approximate the unknown nonlinear dynamics, and a quadratic-fraction barrier Lyapunov function (QFBLF) is introduced to ensure that the predefined state constraints are not violated. Compared with the existing dynamic surface control (DSC) approaches, a novel predefined-time filter and an adaptive fuzzy predefined-time controller are presented, such that the filter error and attitude tracking error can converge to a small region in predefined time simultaneously, where the minimum upper bound of settling time can be exactly preset by tuning one control parameter. Comparative simulation results are carried out to verify the superiority and efficacy of the presented strategy.

In this article, a neural-network-based adaptive fixed-time control scheme is proposed for the attitude tracking of uncertain rigid spacecrafts. A novel singularity-free fixed-time switching function is presented with the directly nonsingular property, and by introducing an auxiliary function to complete the switching function in the controller design process, the potential singularity problem caused by the inverse of the error-related matrix could be avoided. Then, an adaptive neural controller is developed to guarantee that the attitude tracking error and angular velocity error can both converge into the neighborhood of the equilibrium within a fixed time. With the proposed control scheme, no piecewise continuous functions are required any more in the controller design to avoid the singularity, and the fixed-time stability of the entire closed-loop system in the reaching phase and sliding phase is analyzed with a rigorous theoretical proof. Comparative simulations are given to show the effectiveness and superiority of the proposed scheme.