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Aiming at the probe docking control problem in aerial recovery, this article proposes a neural-adaptive probe dynamics direct control algorithm with preassigned docking performance for the unmanned aerial vehicle (UAV) to be recovered, even under multiple ambient airflow disturbances and initial docking deviations. The affine nonlinear dynamics of the probe in the inertial axis are formulated, together with the UAV's 6-DOF dynamics, for the convenience of the direct nonlinear docking control design. To compensate UAV's unmeasurable nonlinear dynamics with better approximation property and lower computational burden, the minimal learning parameter (MLP) technique based echo state network (ESN) approximators are constructed by employing the system state approximation errors to adaptively update neural weights learning. Then, to guarantee the preassigned docking performance required by the recovery safety, a finite-time prescribed performance control algorithm incorporated backstepping control law is developed to achieve the desired docking. Both the docking trajectory and forward docking velocity are not only always constrained within the preassigned performance constraints but also finely controlled to achieve accurate rendezvous with the target drogue. The closed-loop stability is discussed with Lyapunov analysis. Numerical simulations are conducted to validate the performance of the docking control algorithm. [ABSTRACT FROM AUTHOR]

This article contrives a neural-adaptive constrained controller of the cable towed air–ground recovery system subject to terrain obstacles, unmeasurable cable tensions, trailing vortex, wind gust, and actuator saturation. In air–ground recovery system modeling, the towed vehicle's nominal 6 DOF affine nonlinear dynamics and the cable system's finite links-joints dynamics are formulated. To achieve accurate air–ground recovery under terrain obstacles, an asymmetric barrier Lyapunov function-based flight controller of the towed vehicle is proposed, by transforming the terrain obstacles into time-varying constraints on the vehicle's trajectory. Then, to approximate the towed vehicle's lumped unknown dynamics caused by the unmeasurable cable tensions and airflows, several echo state network (ESN) approximators are established for velocity and attitude subsystems. By using the state approximation errors-based neural weights learning strategy and minimal learning parameter technique, these ESNs possess better transient behaviors and lower online computational burden. Furthermore, the actuator saturation is automatically monitored and released, by incorporating a specially designed auxiliary compensating system into the angular rate control law for compensation. The stability of the closed-loop system is analyzed. Finally, numerical simulations under two air–ground recovery scenarios are performed to demonstrate the performance of the proposed controller. [ABSTRACT FROM AUTHOR]

During the pivotal docking process of autonomous aerial refueling (AAR), the flexible refueling hose's transient vibration resulted from the receiver aircraft's excessive closure speed must be immediately suppressed once it appears, due to its disastrous refueling accident possibility. This paper proposes a permanent magnet synchronous motor (PMSM) driven active vibration control scheme for the flexible refueling hose, via the robust integral of the sign of the error (RISE) feedback control and extended state observer (ESO). The active vibration control scheme can suppress the transient hose vibration under multiple disturbances, without angular velocity measurement. The unmeasured load torque is estimated and compensated via the ESO, together with other uncertainties. The proposed method takes advantages from both the disturbance observer-based control and RISE based disturbance suppression control, which tactfully bridge the gap between these two different anti-disturbance control methods. Extensive simulations results demonstrate that the proposed method can rapidly suppress the hose vibration with satisfactory accurately, even in the presence of the probe position perturbation and parametric uncertainties. [ABSTRACT FROM AUTHOR]

Abstract This paper investigates the anti-disturbance constrained trajectory flight control for the ultra-low altitude airdrop under airflow disturbances, by innovatively integrating the finite time convergent high-order sliding mode observer and barrier Lyapunov function-based back-stepping technique. The dynamics of transport aircraft during the airdrop are established based on the fixed-wing aircraft's 6 DOF nonlinear model and are transformed into the affine nonlinear form for the convenient control design. These dynamics include the complex influence of the flow disturbances, the ground effect, the consecutive movement and abrupt extraction of the heavy cargo. Then, the flight controller is divided into several cascade subsystems via back-stepping technique. The items reflect the disturbances during the drop in each subsystem, as well as the items which are independent of the predefined virtual control variables, are taken as components of the "lumped disturbances" which are estimated and compensated by the specially designed finite time convergent high order sliding mode observer. On this basis, a barrier Lyapunov function-based back-stepping flight controller is proposed for the robust and safe flight control of the ultra-low altitude airdrop. And the closed-loop stability is discussed via the Lyapunov stability theorem. Simulation comparisons are conducted to verify the robustness and effectiveness of the proposed airdrop flight control method. [ABSTRACT FROM AUTHOR]

This paper proposed a probe motion compound control scheme for the receiver docking control in the autonomous aerial refueling (AAR). The dynamic equation of the probe is modeled based on the receiver's 6 DOF nonlinear model which considers the influence of the multiple flow disturbance, and these dynamic equations are transformed into the affine nonlinear form for convenient control design. The AAR docking flight controller is divided into several cascade subsystems via back-stepping design technique. The terms which are independent of the virtual control variables in each affine nonlinear subsystem are taken as the “lumped disturbance”, and are accurately estimated for the disturbance compensation in the designed flight controller, by a group of extended states observers (ESO). Then a compound control scheme, which is constituted by back-stepping and ESO, is proposed for AAR docking based on these established receiver dynamics affine nonlinear form and the estimated lumped disturbances by ESOs. In the proposed probe compound scheme, the probe motion is controlled not only via the translational motion of the barycenter but also via the rotational motion of the receiver. The stability of the proposed probe compound control closed-loop system is formally proved by using Lyapunov function technique. Extensive simulations are carried out to verify the effectiveness and improvement with the proposed controller. [ABSTRACT FROM AUTHOR]

In autonomous aerial refueling (AAR), the vibration of the flexible refueling hose caused by the receiver aircraft’s excessive closure speed should be suppressed once it appears. This paper proposed an active control strategy based on the permanent magnet synchronous motor (PMSM) angular control for the timely and accurate vibration suppression of the flexible refueling hose. A nonsingular fast terminal sliding-mode (NFTSM) control scheme with adaptive extended state observer (AESO) is proposed for PMSM take-up system under multiple disturbances. The states and the “total disturbance” of the PMSM system are firstly reconstituted using the AESO under the uncertainties and measurement noise. Then, a faster sliding variable with tracking error exponential term is proposed together with a special designed reaching law to enhance the global convergence speed and precision of the controller. The proposed control scheme provides a more comprehensive solution to rapidly suppress the flexible refueling hose vibration in AAR. Compared to other methods, the scheme can suppress the flexible hose vibration more fleetly and accurately even when the system is exposed to multiple disturbances and measurement noise. Simulation results show that the proposed scheme is competitive in accuracy, global rapidity, and robustness. [ABSTRACT FROM AUTHOR]

This paper proposes a novel back-stepping based flight controller for the receiver in Autonomous Aerial Refueling (AAR) by the combination of active disturbance rejection control (ADRC) and preview control methodology. Firstly, the proposed flight control law design is divided into five loops by the back-stepping technique. The 6 DOF model for aircraft is written into several strict-feedback nonlinear forms through tactful transformation, considering that the path dynamics are originally non-affine nonlinear forms and are intractable for controller design. Secondly, the influences of the unknown flow perturbations on a receiver in each loop are viewed as the components of the “total disturbances” which are estimated and compensated by extended state observer (ESO). Thirdly, the preview control methodology is introduced into the position loop design as the system dynamic of the receiver is much slower than drogue. The position loop determines the proper reference path angle by using a fuzzy-logic ADRC controller in which previewing error and current tracking error are both taken into consideration. And a novel adaptive look-ahead distance scheme based on the fuzzy logic control (FLC) is proposed for the selection of the preview point. Finally, extensive simulations and comparisons on the 6 DOF receiver model are carried out to demonstrate the effectiveness of the proposed flight controller. [ABSTRACT FROM AUTHOR]

This paper proposes a novel robust back-stepping based trajectory tracking controller for the tanker with strict posture constraints under unknown flow perturbations in Autonomous Aerial Refueling (AAR). Firstly, by using the back-stepping technique, the proposed trajectory tracking control law design is separated into five loops. The 6 DOF model for tanker is tactfully transformed into several strict-feedback nonlinear forms, especially the dynamics of the translational kinematics which are originally non-affine nonlinear forms and are intractable for controller design. The influences of the unknown flow perturbations on tanker in each loop are viewed as the components of the “total disturbances” which are estimated and compensated by extended state observer (ESO). Secondly, the uncontrolled Euler angle constraints, which should also be considered in AAR, are transformed into extra boundary commands for the angular rates. And a novel command limiting tracking differentiator (CLTD), which considers not only the controlled but also uncontrolled state constraints, is specially designed for posture control. Thirdly, an integrated robust constrained posture control scheme is proposed for tanker's posture constraints based on Barrier Lyapunov (BL) function and CLTD. Then, with the position and ground velocity controller based on traditional active disturbance rejection control (ADRC) in the outer loop, a novel robust back-stepping based trajectory tracking controller is proposed for tanker in AAR. Finally, extensive simulations and comparisons on the 6 DOF tanker model are carried out to demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper focuses on the fault-tolerant control of the multi-quadrotors cooperative payload transportation under suspension failures. A dynamic load reassignment and control strategy is proposed for the cooperative quadrotors by incorporating the high-order sliding mode disturbance observer into a dynamic surface control-based backstepping design. The dynamics of the cable - suspended payload transportation with multiple quadrotors are formulated. The unmeasurable suspension cable tensions, which will greatly impact the quadrotors' dynamics and stability, are respectively viewed as one part of the lumped disturbance and estimated by the super-twisting sliding mode-based finite-time disturbance observers. With the estimated disturbance compensation, the dynamic surface control laws are established for the cooperative quadrotors. Moreover, to guarantee the fault-tolerant control under suspension cable broken, a dynamic load assignment strategy is proposed to stably recover the cooperative load transportation. Finally, the stability of tethered quadrotors' flight control systems is analyzed. The simulation results show the effectiveness of the proposed algorithm under suspension failures. [ABSTRACT FROM AUTHOR]

The carrier aircraft's accurate control plays a fundamental and vital role during the air recovery of swarm unmanned aerial vehicles. To handle the control problem of the air recovery carrier with trajectory and posture constraints under unknown complex airflow disturbances, this paper proposes a robust constrained flight controller by integrating the integral Barrier Lyapunov function (iBLF) based dynamic surface control (DSC) method with the high-order sliding mode disturbance observer. Firstly, the carrier's six DOF affine nonlinear dynamics considering the unknown airflow disturbances are established for controller design convenience. Secondly, several finite-time convergent super-twisting sliding mode observers are designed to accurately observe the "lumped disturbances" in each subsystem composed of the airflow effect and other unmeasured items. Then, by taking these estimated disturbances as a kind of feed-forward compensating signals, an iBLF-based DSC is established for the carrier's constrained flight required by the specific air recovery mission. Moreover, closed-loop stability is analyzed. Finally, the flight simulations are performed to show the constrained control performance and the anti-disturbance ability of the proposed carrier flight controller, even under unknown airflow disturbances. [ABSTRACT FROM AUTHOR]

Abstract In the autonomous aerial refueling (AAR) docking process, the bow wave generated by the receiver has a strong effect on the drogue, which affects the docking success rate greatly. Thus, a deep learning based trajectory optimization method which aims to decrease the bow wave effect on the drogue is proposed in this paper. There are mainly three parts in the proposed trajectory optimization method. Firstly, a precise bow wave model based on deep learning is presented to estimate the bow wave effect on the drogue. Furthermore, due to the dynamic characteristic of the drogue, a simple and practical drogue motion prediction model under multiple disturbances is carried out to provide a precise prediction of the drogue position at the next time. Moreover, considering the strict attitude constraints requirements in the AAR docking process, a novel reference observer is designed to estimate the receiver attitude from the optimized trajectory under wind perturbations. Then, the proposed trajectory optimization method could not only diminish the bow wave effect on the drogue largely but also satisfy the attitude constraints of the receiver. Finally, the effectiveness of the proposed method is demonstrated by the simulations. [ABSTRACT FROM AUTHOR]

This paper proposes an active disturbance rejection control (ADRC) scheme for automatic carrier landing system (ACLS) in final approach. To track desired touchdown point (DTP) altitude in the presence of carrier air wake turbulence and deck motion, based on the estimation and compensation of internal dynamics and external disturbances by extended state observer (ESO), outer-loop altitude controller and inner-loop attitude controllers are designed via ADRC. Moreover, tracking differentiator-based deck motion compensation (TD-DMC) is designed to eliminate the inherent phase lag in ACLS. In addition, controller parameters are optimized via a novel Levy flight based whale optimization algorithm (LWOA). Finally, comparative simulations demonstrate that the proposed ADRC-based ACLS has better tracking performance and robustness compared to conventional ACLS. [ABSTRACT FROM AUTHOR]

In this paper, we propose a hybrid approach based on the Lyapunov Guidance Vector Field (LGVF) and the Improved Interfered Fluid Dynamical System (IIFDS), to solve the problems of target tracking and obstacle avoidance in three-dimensional cooperative path planning for multiple unmanned aerial vehicles (UAVs). First, LGVF method is improved for UAV cooperative target tracking in 3D environment by introducing vertical component, with two guidance layers containing steering control and speed control. Second, IIFDS method is presented for UAVs to avoid obstacles or threats in complicated environment, where the local minimum problem is well resolved. Moreover, some cooperative strategies are added into the IIFDS framework to satisfy the constraints of obstacle avoidance and cluster maintenance. Finally, the missions of tracking target and avoiding obstacles can be performed simultaneously, by replacing the original sink fluid of IIFDS with the vector field of LGVF. Besides, the reactive parameters of IIFDS can be adjusted by the rolling optimization strategy to enhance the path quality. The experimental results validate the effectiveness of the hybrid method. [ABSTRACT FROM AUTHOR]

According to the tactical requirements of unmanned aerial vehicle (UAV) for tracking target and avoiding obstacle in complex dynamic environment, a three-dimensional (3D) real-time path planning method is proposed by combing the improved Lyapunov Guidance Vector Field (LGVF), the Interfered Fluid Dynamical System (IFDS) and the strategy of varying receding-horizon optimization from Model Predictive Control (MPC). First, in order to track the moving target in 3D environment, the LGVF method is improved by introducing flight height into the traditional Lyapunov function, and the generated velocity can guide UAV converge gradually to the limit cycle in horizontal plane and the optimal height in vertical plane. Then, the IFDS method imitating the phenomenon of fluid flow is utilized to plan the collision-free path. To achieve the mission of tracking moving target and avoid static or dynamic obstacle at the same time, the guidance vector field by LGVF is taken as the original fluid of IFDS. As the fluid system still remains stable under the influence of obstacles, the disturbed streamline from the interfered fluid can be regarded as the planned path. Third, as the quality of route is mainly influenced by the repulsive and tangential parameters of IFDS, the real-time suboptimal route can be planned by the varying receding-horizon optimization according to the predicted motion. The experimental results prove that the proposed hybrid method is applicable to various dynamic environments. [ABSTRACT FROM AUTHOR]

In this study, two types of three-dimensional (3-D) flight-based energy management strategies for solar-powered unmanned aerial vehicle (SUAV) long-endurance target tracking are proposed. In SUAV dynamic modeling, we consider the influence of wind on SUAV kinematics. Aiming at the complexity of the long-endurance tracking, namely the long flight time and space spans, the influences of the wind, variations of temperature, air density and solar cell photovoltaic efficiency, and a finite battery capacity are considered in our modified SUAV energy model. Then, considering the mission flexibility, we design two types of energy management strategies that comprehensively utilize the solar energy, gravitational potential energy, and wind to address different situations. The proposed strategies can be divided into several stages in chronological order according to the solar irradiation conditions, electrical energy storage conditions, and relative motion relationships among the SUAV, target, and wind. We then design respective strategies for these stages. The core of our proposed energy management strategies is to design the corresponding objective functions in each stage and the switching conditions between adjacent stages. Finally, we verify our proposed strategies by comparison with the traditional 2-D tracking strategy in a 24-h target tracking mission, and the results show the validity of our proposed strategies. [ABSTRACT FROM AUTHOR]

In this paper, a scheme which combines finite-time model-assisted active disturbance rejection control and novel greedy criterion-based salp swarm algorithm is developed for attitude tracking problem of hypersonic reentry vehicle with multiple disturbances. To simplify control structure, the control scheme is designed within the framework of active disturbance rejection control completely. To lessen tuning parameters, a sigmoid function-based tracking differentiator is employed to generate a more realizable attitude transient profile instead of utilizing conventional nonlinear tracking differentiator. Taking known model information as model-assisted term, finite-time model-assisted extended state observers are constructed to estimate the lumped disturbance in attitude and angular rate loop with employment of function fal . To achieve rapid response and strong robustness, finite-time model-assisted control laws are derived by utilizing function fhan . Finally, a novel greedy criterion-based salp swarm algorithm is used to optimize control parameters in finite-time model-assisted control laws to achieve optimal solution that minimizes the tracking error and energy consumption. Comparative simulations are conducted to illustrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

Aiming at the trajectory optimization of the solar-powered UAVs (SUAVs) cooperative target tracking in urban environment, the distributed model predictive control (DMPC) method based on Adaptive Grasshopper Optimization Algorithm (AGOA) is proposed in this paper. Firstly, the cooperative target tracking problem in urban environment is modeled by formulating the SUAVs kinematic and target models, the urban environment constraints, solar power harvesting and consumption models for SUAV, and sight occlusions by constructions. Especially, the sight occlusions in urban environment for SUAV are taken into consideration for the first time in this paper. A judgment method of sight occlusions for SUAV is proposed to make the calculation of the energy index more precise. Second, based on the precise modeling, the DMPC method is adopted as the framework for trajectory optimization in real time. Third, AGOA, a novel intelligent algorithm to mimic the behaviors of grasshoppers, is proposed to be the DMPC solver. The proposed AGOA has a better searching ability than the traditional GOA and some other intelligent algorithms by introducing some improvement measures e.g. the natural selection strategy, the democratic decision-making mechanism, and the dynamic feedback mechanism based on the 1/5 Principle. Finally, the effectiveness of the proposed method is demonstrated by the simulations. [ABSTRACT FROM AUTHOR]

An efficient enhancement and broadening 3 μm luminescence in the Er/Ho/Pr: PbF 2 crystal was obtained for the first time. The 3 μm emission characteristics and energy transfer mechanism of the as-grown crystals were investigated in details. It shows that the introduced Er3+ ion can not only act as a sensitizer for Ho3+ ion to allow the crystal to be pumped by a 980 nm laser diode, but also broaden the 3 μm fluorescence emission. Moreover, the Pr3+ ions can also act as a suitable deactivated ion for Er3+ and Ho3+ ions, bringing about the enhancing of 3 μm fluorescence emission. These results suggest that the Er/Ho/Pr: PbF 2 crystal may have potential applications around 3 μm broadband lasers. • Optical characteristics of Er/Ho/Pr: PbF 2 as 3 μm laser crystal was evaluated. • The mechanism of energy transfer between Er3+, Ho3+, and Pr3+ was investigated. • Er3+/Ho3+ ions broaden 3 μm fluorescence as co-luminescence centers. • An enhanced broadband emission with large effective bandwidth(330 nm) was obtained. [ABSTRACT FROM AUTHOR]