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The challenging problem of attitude tracking control for unmanned space vehicles (USVs) subject to actuator faults and output constraints is addressed in this study. A novel adaptive neural fault-tolerant controller is proposed by integrating the neural networks (NNs) and barrier Lyapunov function (BLF) with the backstepping technique. Two NNs are adopted to approximate the uncertain nonlinear terms caused by unknown attitude dynamics and actuator faults, respectively. Moreover, the BLF is introduced to tackle the output constraints. It is strictly proved that all the closed-loop error signals are uniformly ultimately bounded under the proposed controller. Totally, the proposed adaptive neural fault-tolerant controller has the following two distinctive features. (1) The proposed controller is model-free and can still be applicable even when the USV attitude dynamic model is completely unknown in advance. (2) The proposed controller can guarantee the attitude tracking error always within the predefined output constraints even in the presence of actuator faults and thus ensuring safety. Finally, the excellent tracking performance of the proposed controller is verified through numerical simulations and comparisons. [ABSTRACT FROM AUTHOR]

This paper proposes a novel neural adaptive fixed-time control approach for the attitude stabilization and vibration suppression of flexible spacecraft. First, the neural network (NN) was introduced to identify the lumped unknown term involving uncertain inertia, external disturbance, torque saturation, and elastic vibrations. Then, the proposed controller was synthesized by embedding the NN compensation into the fixed-time backstepping control framework. Lyapunov analysis showed that the proposed controller guaranteed the stabilization of attitude and angular velocity to the adjustable small neighborhoods of zero in fixed time. The proposed controller is not only robust against uncertain inertia and external disturbance, but also insensitive to elastic vibrations of the flexible appendages. At last, the excellent stabilization performance and good vibration suppression capability of the proposed control approach were verified through simulations and detailed comparisons. [ABSTRACT FROM AUTHOR]

In this paper, we present an adaptive control strategy for the output-constrained attitude tracking of rigid spacecraft under unknown inertia and disturbances. The designed controller is recursively constructed under the framework of the backstepping method, which involves an auxiliary stabilizing law and a practical control law. In the auxiliary stabilizing law design, the log-type barrier Lyapunov function (BLF) is embedded to tackle the time-varying output constraints. In addition, in the practical control law design, the element-wise parametric adaptive laws are adopted to identify the unknown inertia and disturbances by introducing a linear mapping operator. The stability evaluation indicates that the overall closed-loop system is semi-globally uniformly ultimately bounded (SGUUB) and all error variables can eventually regulate to the minor fields about zero. Meanwhile, the spacecraft attitude tracking errors can be preserved in the preassigned output constraints. Lastly, the efficiency and strong robustness of the presented control strategy are demonstrated through competitive simulations. [ABSTRACT FROM AUTHOR]

In this article, a distributed adaptive fault-tolerant control scheme is presented for the attitude consensus of multiple flexible spacecraft formulated by partial differential equations (PDEs). Each spacecraft is supposed to be actuated by a control torque on the rigid hub and a control force on the tip payload. First, a finite-time distributed observer is constructed to estimate the virtual leader's state for each follower spacecraft under local communication. Then, an individual controller is exploited for each follower spacecraft, which consists of an adaptive boundary control torque law to track the recovered attitude and velocity and an adaptive boundary control force law to eliminate the elastic deformation. Particularly, the parametric adaptation laws are incorporated to compensate the actuator faults and perturbations. The attitude synchronization errors, velocity synchronization errors, and elastic deformations can asymptotically stabilize to zero under the introduced controller. This work owns the following two major novelties. One is introducing a unified distributed control framework for the PDE-based attitude consensus of multiple flexible spacecraft. Another is developing a novel parametric adaptation strategy to accommodate the actuator faults. Lastly, comparative simulations verify and highlight the main results. [ABSTRACT FROM AUTHOR]

This article presents a prescribed performance adaptive control scheme for the attitude tracking and vibration reduction of flexible spacecraft modeled by partial differential equations (PDEs). First, the original constrained problem is converted to an equivalent unconstrained one by adopting a prescribed error transformation. Then, a boundary control torque law and a boundary control force law are developed to track the desired attitude and reduce the vibration, respectively. Moreover, the parametric adaptation technique is integrated with the boundary control laws to estimate the disturbances. The closed-loop system is evaluated to be asymptotically stable through the Lyapunov stability theorem and LaSalle's invariance principle. The developed controller has two distinctive features as follows. One is the controller can guarantee the attitude tracking error and tip deformation always satisfy the prescribed performance constraints. Another is the controller can acquire the strong robustness owing to the feedforward disturbance compensation. Lastly, the derived results are demonstrated by simulated studies. [ABSTRACT FROM AUTHOR]

In this paper, a neural adaptive fault-tolerant control scheme is proposed for the integrated attitude and position control of spacecraft proximity operations in the presence of unknown parameters, disturbances, and actuator faults. The proposed controller is made up of a relative attitude control law and a relative position control law. Both the relative attitude control law and relative position control law are designed by adopting the neural networks (NNs) to approximate the upper bound of the lumped unknowns. Benefiting from the indirect neural approximation, the proposed controller does not need any model information for feedback. In addition, only two adaptive parameters are required for the indirect neural approximation, and the online calculation burden of the proposed controller is therefore significantly reduced. Lyapunov analysis shows that the overall closed-loop system is ultimately uniformly bounded. The proposed controller can ensure the relative attitude, angular velocity, position, and velocity stabilize into the small neighborhoods around the origin. Lastly, the effectiveness and superior performance of the proposed control scheme are confirmed by a simulated example. [ABSTRACT FROM AUTHOR]