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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]

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 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]