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The purpose of this paper is to present a small UAV system with autonomous formation flight capability, the Swallow UAV system, and the application of an extended Kalman filter (EKF) based augmentation method to reduce the impact of data link loss, which will fail the formation flight algorithm of the system.

The hardware of the Swallow UAV system is composed of two aircraft and a set of ground control station for leader‐wingman formation flight. A hardware‐in‐the‐loop simulation environment is build to support the system development. Fuzzy logic control method is applied to the guidance, navigation, and control system of leader and wingman aircraft. The leader system is designed with waypoint navigation and circle trajectory tracking functions to make the aircraft stay in visual range autonomously for safety. The wingman system is designed with formation flight functionality. However, the relative position and velocity are derived from the wireless data link transmitted leader navigation information. It is vulnerable to the data link loss. The EKF based leader motion estimator (LME) is developed to estimates the leader position when the data link broke, and corrects the estimation when the data link is available.

The designed LME is flight tested, and the results show that it woks properly with sound performance that the estimation error of relative position within 3 meters, relative velocity within 1.3 meters, and leader attitude within 1.6 degrees in standard deviation.

The research implements the autonomous formation flight capability with the EKF based LME on a small UAV system.

This paper aims to study the issue of the three-dimensional formation coordinated control for the unmanned autonomous helicopter (UAH) by using the sliding mode disturbance observer. Under the designed formation coordinated controller, the desired formation can be maintained and the closed-loop system stability is analyzed by using the Lyapunov theory.

Considering the unknown time-varying external 10; disturbance in formation flight of UAHs, a sliding mode disturbance observer has been employed to estimate them.

This work is supported in part by the National Natural Science Foundation of China under Grant 61803207, and in part by the Fundamental Research Funds for the Central Universities under Grant LGZD201806.

A sliding mode disturbance observer has been designed to estimate the unknown time-varying external disturbance in formation flight of UAHs. Aiming at the leading UAH maneuver in three-dimensional space during the formation flight progress, the formation coordinated controller has been proposed based on the output of the disturbance observer to maintain the formation.

The purpose of this paper is to study the potential advantages of aircraft formation flight (FF) and to exploit further benefits through exchanging the leading positions.

The detailed and robust methodologies concerning FF mission analysis including the leading aircraft rotation strategies are developed in this paper to study the fuel burn benefit and the additional bonus of formation rotation.

Switch of FF leading positions can offset the undesired weight ratios between the leading and trailing aircraft within FF missions, which further alleviates the deviations from design flight conditions. The case studies on two long-range civil transport aircraft in FF show that the leading and trailing aircraft can achieve almost equal fuel benefit through rotations. As compared to FF without rotation, the fuel efficiency can be improved by more than 11 per cent.

The work can bring benefit the research communities as a fundamental basis for operational studies of FF, such as FF airspace management in the future, which is significant for a future real-world implementation of FFs.

According to the authors’ study, equal or quasi-equal fuel savings can be achieved if the rotation is properly arranged. For the real-world FF application, fuel consumption (FC) or cost redistribution problem for leading and trailing aircraft belonging to two different operating airlines can therefore be resolved through the concept proposed by the paper.

The methods developed in the paper have the advantage to give more reliable estimations of the achievable fuel burn savings of FF. The concept proposed in the paper has significant meaning with respect to offset the undesired weight ratios between the leading and trailing aircraft within FF missions and redistributing FC or cost redistribution of different operating airlines.

The purpose of this paper is to design an integrated guidance and control design for a formation flight of four unmanned aerial vehicles to follow a moving ground target.

The guidance law is based on the line‐of‐sight. The control is optimal. The guidance law is integrated with the optimal control law and is applied to a linear dynamic model.

The theoretical results are supported by the numerical simulations that illustrate a coordinated encirclement of a ground maneuvering target.

A linear dynamic UAV model and a liner engine model were employed.

This is expected to provide efficient coordination technique required in many civilian circular formation UAV applications; also the technique can be used to provide a safe environment required for the civil applications.

The research will facilitate the deployment of autonomous unmanned aircraft systems in various civilian applications such as border monitoring.

The research addresses the challenges of coordination of multiple unmanned aerial vehicles in a circular formation using an integrated optimal control technique with line‐of‐sight guidance.

The purpose of this paper is to construct an event-triggered finite-time fault-tolerant formation tracking controller, which can achieve a time-varying formation control for multiple unmanned aerial vehicles (UAVs) during actuator failures and external perturbations.

First, this study developed the formation tracking protocol for each follower using UAV formation members, defining the tracking inaccuracy of the UAV followers’ location. Subsequently, this study designed the multilayer event-triggered controller based on the backstepping method framework within finite time. Then, considering the actuator failures, and added self-adaptive thought for fault-tolerant control within finite time, the event-triggered closed-loop system is subsequently shown to be a finite-time stable system. Furthermore, the Zeno behavior is analyzed to prevent infinite triggering instances within a finite time. Finally, simulations are conducted with external disturbances and actuator failure conditions to demonstrate formation tracking controller performance.

It achieves improved performance in the presence of external disturbances and system failures. Combining limited-time adaptive control and event triggering improves system stability, increase robustness to disturbances and calculation efficiency. In addition, the designed formation tracking controller can effectively control the time-varying formation of the leader and followers to complete the task, and by adding a fixed-time observer, it can effectively compensate for external disturbances and improve formation control accuracy.

A formation-following controller is designed, which can handle both external disturbances and internal actuator failures during formation flight, and the proposed method can be applied to a variety of formation control scenarios and does not rely on a specific type of UAV or communication network.

The purpose of this paper is to analyze the frame of a missile formation cooperative control system, and present an optimal keeping controller of a missile formation in the cooperative engagement.

A missile relative motion model is established directly based on the kinematics relationships in the relative coordinated frame, following that is the detailed process of designing an optimal formation controller, which is analyzed through the small disturbance linearized method and transforming control variables method, respectively, these two methods both have themselves properties. The equations and control variables are intuitive during the linearized analysis, but errors brought by the linearized method are unavoidable, which will reduce the control precision. As for the transforming method, the control accuracy is greatly increased although the control form is a little complex, so in this paper the transforming control variable method is mainly researched to design an optimal formation controller. Considering the states of a leader as input perturbation variables, we design an optimal formation controller based on the linear quadric theory, which has quadric optimal performances of the missile flight states and control quantity. In order to obtain a higher accurate solution, the precise integration algorithm is introduced to solve the Riccati Equation that significantly affects the accuracy of an optimal control problem.

The relative motion model established directly in the relative coordinate frame has intuitive physical significance, and the optimal controller based on this relative motion model is capable of restraining the invariable or slowly varying perturbation brought by the velocity of a leader and the input perturbations caused by the maneuver of the leader, at the same time this optimal controller can implement formation reconfiguration and keeping to an expected states rapidly, steadily and exactly; the steady errors can be greatly decreased by analyzing the relative motion model through transforming control variables method compared to the small disturbance linearized operation.

The main frame of a missile formation cooperative engagement system can be found in this paper, which shows a clear structure and relations of each part of this complex system. The relations between each subsystem including the specific input and output variables can also be used to guide and restrict how to design each subsystem. The emphasis of this paper is on designing an optimal formation keeping controller which can overcome slowly varying or invariable perturbations and implement quadric optimal keeping control rapidly, stably and accurately.

This paper provides a new method to analyze the missile relative motion model. The proposed proportional and integral (PI) optimal controller based on this model, and utilizing the Precise Integration Algorithm to solve this optimal controller are also new thoughts for formation control problems.

The purpose of this paper is to deal with the anomaly detection problem in multi-unmanned aerial vehicles (UAVs) formation that can be transformed to identify some unknown parameters; a more general nonlinear dynamical model for each UAV is considered to include two terms. Due to an unknown parameter corresponding to the normal or abnormal state for each UAV, the bias-compensated approach is proposed to obtain the unbiased parameter estimation. Meanwhile, the biased error and accuracy analysis are also given in case of strict statistical description of the uncertainty or white noise. To relax this strict statistical description on external noise, an analytic center approach is proposed to identify the unknown parameters in presence of bounded noise, such that two inner and outer ellipsoidal approximations are constructed to include the membership set. To be precise, this paper is regarded as one extension and summary for the author’s previous research on the anomaly detection in multi-UAV formation. Finally, one simulation example is given to confirm the theoretical results.

Firstly, one extended nonlinear relation is constructed to embody the mutual relationship of UAVs. Secondly, to obtain the unbiased parameter estimations, the bias-compensated approach is applied to achieve it under the condition of white noise. Thirdly, in case of unknown but bounded noise, an analytic center approach is proposed to deal with this special case. Without loss of generality, the author thinks this paper can be used as one extension and summary for research on multi-UAVs formation anomaly detection.

An anomaly detection problem in multi-UAVs formation can be transformed into a problem of nonlinear system identification, and in modeling the nonlinear dynamical model for each UAV, two terms are considered simultaneously to embody the mutual relationships with other nearest UAV.

To the best knowledge of the authors, this problem of the anomaly detection problem in multi-UAVs formation is proposed by the authors’ previous work, and the problem of multi-UAVs formation anomaly detection can be transferred into one problem of parameter identification. In case of unknown but bounded noise, an analytic center approach is proposed to identify the unknown parameters, which correspond to achieve the goal of the anomaly detection.

This new paper aims to combine the recent new contributions about direct data driven control and other safety property to form an innovative direct data driven safety control for aircraft flight system. More specifically, within the framework of direct data driven strategy, the collected data are dealt with to get the identified plant and designed controller. After reviewing some priori information about aircraft flight system, a closed loop system with the unknown plant and controller simultaneously is considered. Data driven estimation is proposed to identify the plant and controller only through the ratios of two correlation functions, computed from the collected data. To achieve the dual missions about perfect tracking and safety property, a new notion about safety controller is introduced. To design this safety controller, direct data driven safety controller is proposed to solve one constrain optimization problem. Then the authors apply the Karush–Kuhn–Tucker (KKT) optimality conditions to derive the explicit safety controller.

First, consider one closed loop system corresponding to aircraft flight system with the unknown plant and feed forward controller, data driven estimation is used to identify the plant and feed forward controller. This identification process means nonparametric estimation. Second, to achieve the perfect tracking one given transfer function and guarantee the closed loop output response within one limited range simultaneously, safety property is introduced. Then direct data driven safety control is proposed to design the safety controller, while satisfying the dual goals. Third, as the data driven estimation and direct data driven safety control are all formulated as one constrain optimization problem, the KKT optimality conditions are applied to obtain the explicit safety controller.

Some aircraft system identification and aircraft flight controller design can be reformulated as their corresponding constrain optimization problems. Then through solving these constrain optimization problems, the optimal estimation and controller are yielded, while satisfying our own priori goals. First, data driven estimation is proposed to get the rough estimation about the plant and controller. Second, data driven safety control is proposed to get one safety controller before our mentioned safety concept.

To the best of the authors’ knowledge, some existing theories about nonparametric estimation and tube model predictive control are very mature, but few contributions are applied in practice, such as aircraft system identification and aircraft flight controller design. This new paper shows the new theories about data driven estimation and data driven safety control on aircraft, being corresponded to the classical nonparametric estimation and tube model predictive control. Specifically, data driven estimation gives the rough estimations for the aircraft and its feed forward controller. Furthermore, after introducing the safety concept, data driven safety control is introduced to achieve the desired dual missions with the combination of KKT optimality conditions.

THE flight of a formation of seaplanes to America and back, recently completed by the Italian Air Force under the personal leadership of the Secretary of State for Air, Air Marshal Balbo, is one of those performances which can be accorded wholehearted approval.

The purpose of this paper is to propose a new algorithm for linear-quadratic regulator (LQR) controller of a quadrotor with fast and stable performance, which is based on pigeon-inspired optimization (PIO).

The controller is based on LQR. The determinate parameters are optimized by PIO, which is a newly proposed swarm intelligent algorithm inspired by the characteristics of homing pigeons.

The PIO-optimized LQR controller can obtain the optimized parameters and achieve stabilization in about 3 s.

The PIO-optimized LQR controller can be easily applied to the flight formation, autonomous aerial refueling (AAR) and detection of unmanned aerial vehicles, especially applied to (AAR) in this paper.

This research applies PIO to optimize the tuning parameters of LQR, which can considerably improve the fast and stabilizing performance of attitude control. The simulation results show the effectiveness of the proposed algorithm.