Path planning and formation control are both challenging and critical issues in robotics, which involve computing an optimal path from the initial position to target while keeping the desired formation. This brief studies the path planning and formation control problem for multiple unmanned aerial vehicles (multi-UAVs) in 3-D constrained space. Considering the local minimum of artificial potential function (APF), an effective improved artificial potential function (IAPF) based path planning approach is proposed for the multi-UAV systems. By introducing a rotating potential field, the UAVs can escape from the common local minimum and oscillations efficiently. Afterwards, by using the leader-follower model, a formation controller based on potential function method is developed to ensure that the follower UAVs keep the desired angles and distances with the leader, and a Lyapunov function is designed to analyze the closed-system stability. Finally, simulation studies under different environmental constraints confirm the efficiency of the proposed approaches in addressing the path planning and formation control issues in 3-D space.

The science objectives of a spacecraft mission place stringent performance requirements on the spacecraft attitude control system. However, it remains an open problem how to guarantee consistent control performance necessary to meet these requirements, especially in the event of actuator faults and input saturation. Motivated by this fact, in this paper, we address the problem of attitude tracking control with prescribed performance guarantees for a rigid spacecraft subject to unknown but constant inertia parameters, unexpected disturbances, actuator faults, and input saturation. First, certain performance functions specified a priori by the designer are adopted to impose desired performance metrics on the attitude tracking errors. Then, the original attitude tracking error dynamics with performance constraints is transformed into an equivalent “state-constrained” one whose robust stabilization is shown to be sufficient to solve the stated problem via a novel error transformation. Subsequently, based on the transformed system, an adaptive fault-tolerant controller is derived by incorporating backstepping control, the barrier Lyapunov function, and Nussbaum gains. It is proved that the designed controller is able to guarantee the satisfaction of the prespecified constraints on the transformed errors, as well as the boundedness of all other closed-loop signals, without resorting to a judicious selection of the control parameters. Finally, the effectiveness of the proposed control scheme is evaluated by means of simulation experiments carried out on a microsatellite.

This brief examines the problem of attitude tracking control with prescribed performance guarantees for a spacecraft subjected to actuator faults and input saturation. To pursue this, the open-loop tracking error dynamics with certain designer-specified performance constraints is first transformed into an equivalent ``state-constrained'' one, via an error transformation; furthermore, the resulting dynamics is augmented with a dynamic system, which is tactfully constructed to ensure that the control input satisfies the magnitude limits. Subsequently, a robust fault-tolerant controller is developed by using a low-pass filter and an auxiliary system in conjunction with adaptive backstepping design. It is shown that the control algorithm developed not only achieves the stable attitude tracking with prescribed behavioral metrics but also guarantees the boundedness of all the closed-loop signals. Finally, simulation results are given to evaluate the efficacy of the proposed scheme.

The capture of a free-floating tumbling object using an autonomous vehicle is a key technology for many future orbital missions. Spacecraft proximity operations will play an important role in guaranteeing the success of such missions. In this paper, we technically propose a tracking control scheme for proximity operations between a target and a pursuer spacecraft that ensures accurate relative position tracking as well as attitude synchronization. Specifically, an integrated six degrees of freedom dynamics model is first established to describe the relative motion of the pursuer with respect to the target. Then, a robust fault-tolerant controller is derived by combining the sliding mode control and the adaptive technique. The designed controller is proved to be not only robust against unexpected disturbances and adaptive to unknown and uncertain mass/inertia properties of the pursuer, but also able to accommodate a large class of actuator faults. In particular, by incorporating a novel time-varying forcing function into the sliding dynamics, the proposed control algorithm is able to guarantee the finite-time convergence of the translational and rotational tracking errors, and the convergence time as an explicit parameter can be assigned a priori by the designers. Furthermore, a theoretical analysis is also presented to assess the fault tolerance ability of the designed controller. Finally, numerous examples are carried out to evaluate the effectiveness and demonstrate the benefits of the overall control approach.

In this article, a novel pose (i.e., concurrent position-attitude) tracking control framework is proposed for spacecraft proximity operations with a freely tumbling target, employing the prescribed performance control (PPC) methodology. Especially, the whole operations involved are divided into two synchronously occurring maneuvers: relative position tracking and boresight pointing adjustment. For the former, a new relative translational dynamics is established to facilitate its problem formulation and solving, while, for the latter, the desired attitude is extracted to align the boresight of the pursuer's onboard vision sensor toward the target. Given this, a noncertainty-equivalence adaptive pose controller is designed based on the PPC design approach integrating a class of appointed-time performance functions. It is shown that the designed controller is able to achieve prescribed performance guarantees for the pose tracking errors and, meanwhile, guarantee asymptotic convergence of both the velocity and angular velocity errors, regardless of mass and inertia uncertainties. The salient feature of the proposed method is that, by judiciously imposing the performance specifications on the pose tracking errors, it can: 1) enable the pursuer to accomplish the proximity operations in a designer-appointed time and 2) ensure compliance with spatial motion constraints and avoid singularity of the attitude extraction algorithm. Finally, simulation results are presented to illustrate the effectiveness of the proposed method.

This article investigates the attitude control problem of a rigid body subject to attitude and angular rate constraints (double-level state constraints), and inertia uncertainties. A data-driven immersion and invariance (I&I) adaptive control scheme is proposed to tackle this technically challenging problem. As a stepping stone, a novel dynamically scaled I&I adaptive controller is designed to bypass the realizability condition that may not hold in the Lyapunov sense when considering angular rate constraints. Lyapunov stability analysis shows that this controller can enable the attitude errors and angular rates to converge asymptotically to zero for most initial conditions in the accessible space, while strictly obeying double-level state constraints with the help of two judiciously constructed potential functions. After that, to further relax the dependence of parameter convergence on the persistent excitation (PE) condition, the I&I adaptive law is extended to a data-driven counterpart through adding a learning term that is acquired by adopting the regressor filtering in conjunction with the dynamic regressor extension and mixing (DREM) procedure. The extended adaptive controller can not only preserve all the results obtained by the earlier proposed I&I adaptive controller, but also ensure asymptotic parameter convergence under a finite excitation condition much weaker than PE. In addition, benefiting from the DREM method and some special designs, the parameter convergence rates across all the parameter vector components can be flexibly tuned in an explicit way, and moreover, they are independent of the excitation level. Finally, simulation results are given to show the effectiveness of the proposed method.