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Article
Publication date: 7 January 2021

Wang Jianhong and Wang Yanxiang

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Details

Aircraft Engineering and Aerospace Technology, vol. 93 no. 1
Type: Research Article
ISSN: 1748-8842

Keywords

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Article
Publication date: 13 November 2017

Tianyi Xiong, Zhiqiang Pu and Jianqiang Yi

The purpose of this paper is to investigate the time-varying finite-time formation tracking control problem for multiple unmanned aerial vehicle systems under switching…

Abstract

Purpose

The purpose of this paper is to investigate the time-varying finite-time formation tracking control problem for multiple unmanned aerial vehicle systems under switching topologies, where the states of the unmanned aerial vehicles need to form desired time-varying formations while tracking the trajectory of the virtual leader in finite time under jointly connected topologies.

Design/methodology/approach

A consensus-based formation control protocol is constructed to achieve the desired formation. In this paper, the time-varying formation is specified by a piecewise continuously differentiable vector, while the finite-time convergence is guaranteed by utilizing a non-linear function. Based on the graph theory, the finite-time stability of the close-loop system with the proposed control protocol under jointly connected topologies is proven by applying LaSalle’s invariance principle and the theory of homogeneity with dilation.

Findings

The effectiveness of the proposed protocol is verified by numerical simulations. Consequently, the proposed protocol can successfully achieve the predefined time-varying formation in finite time under jointly connected topologies while tracking the trajectory generated by the leader.

Originality/value

This paper proposes a solution to simultaneously solve the control problems of time-varying formation tracking, finite-time convergence, and switching topologies.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 10 no. 4
Type: Research Article
ISSN: 1756-378X

Keywords

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Article
Publication date: 7 August 2021

Tagir Z. Muslimov and Rustem A. Munasypov

This paper aims to propose a multi-agent approach to adaptive control of fixed-wing unmanned aerial vehicles (UAVs) tracking a moving ground target. The approach implies…

Abstract

Purpose

This paper aims to propose a multi-agent approach to adaptive control of fixed-wing unmanned aerial vehicles (UAVs) tracking a moving ground target. The approach implies that the UAVs in a single group must maintain preset phase shift angles while rotating around the target so as to evaluate the target’s movement more accurately. Thus, the controls should ensure that the UAV swarm follows a moving circular path whose center is the target while also attaining and maintaining a circular formation of a specific geometric shape; and the formation control system is capable of self-tuning because the UAV dynamics is uncertain.

Design/methodology/approach

This paper considers two interaction architectures: an open-chain where each UAV only interacts with its neighbors; and a cooperative leader, where the leading UAV is involved in attaining the formation. The cooperative controllers are self-tuned by fuzzy model reference adaptive control (MRAC).

Findings

Using open-chain decentralized architecture allows to have an unlimited number of aircraft in a formation, which is in line with the swarm behavior concept. The approach was tested for efficiency and performance in various scenarios using complete nonlinear flying-wing UAV models equipped with configured standard autopilot models.

Research limitations/implications

Assume the target follows a rectilinear trajectory at a constant speed. The speed is supposed to be known in advance. Another assumption is that the weather is windless.

Originality/value

In contrast to known studies, this one uses Lyapunov guidance vector fields that are direction- and magnitude-nonuniform. The overall cooperative controller structure is based on a decentralized and centralized consensus.

Details

Aircraft Engineering and Aerospace Technology, vol. 93 no. 7
Type: Research Article
ISSN: 1748-8842

Keywords

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Article
Publication date: 3 September 2021

Yanjie Chen, Weiwei Zhan, Yibin Huang, Zhiqiang Miao and Yaonan Wang

This paper aims to investigate the distributed formation control problem for a multi-quadrotor unmanned aerial vehicle system without linear velocity feedbacks.

Abstract

Purpose

This paper aims to investigate the distributed formation control problem for a multi-quadrotor unmanned aerial vehicle system without linear velocity feedbacks.

Design/methodology/approach

A nonlinear controller is proposed based on the orthogonal group SE(3) to obviate singularities and ambiguities of the traditional parameterized attitude representations. A cascade structure is applied in the distributed controller design. The inner loop is responsible for attitude control, and the outer loop is responsible for translational dynamics. To ensure a linear-velocity-free characteristic, some auxiliary variables are introduced to construct virtual signals in distributed controller design. The stability analysis of the proposed distributed control method by the Lyapunov function is provided as well.

Findings

A group of four quadrotors with constant reference linear velocity and a group of six quadrotors with varying reference linear velocity are adopted to verify the effectiveness of the proposed strategy.

Originality/value

This is a new innovation for multi-robot formation control method to improve assembly automation.

Details

Assembly Automation, vol. 41 no. 5
Type: Research Article
ISSN: 0144-5154

Keywords

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Article
Publication date: 1 June 2021

Wang Jianhong

The purpose of this paper considers optimal input signal design for flutter model parameters identification, as input signal is the first step during the whole…

Abstract

Purpose

The purpose of this paper considers optimal input signal design for flutter model parameters identification, as input signal is the first step during the whole identification process. According to the constructed flutter stochastic model with observed noises, separable least squares identification and set membership identification are proposed to identify those unknown model parameters for statistical noise and unknown but bounded noise, respectively. The common trace operation with respect to the asymptotic variance matrix is minimized to solve the power spectral for the optimal input signal in the framework of statistical noise. Moreover, for the unknown bout bounded noise, the radius of information, corresponding to the established parameter uncertainty interval, is minimized to give the optimal input signal.

Design/methodology/approach

First, model identification for aircraft flutter is reviewed as one problem of parameter identification and this aircraft flutter model corresponds to one stochastic model, whose input signal and output are corrupted by external noises. Second, for aircraft flutter statistical model with statistical noise, separable least squares identification is proposed to identify the unknown model parameters, then the optimal input signal is designed to satisfy one given performance function. Third, for aircraft flutter model with unknown but bounded noise, set membership identification is proposed to solve the parameter set for each unknown model parameter. Then, the optimal input signal is designed by applying the idea of the radius of information with unknown but bounded noise.

Findings

This aircraft flutter model corresponds to one stochastic model, whose input signal and output are corrupted by external noises. Then identification strategy and optimal input signal design are studied for aircraft flutter model parameter identification with statistical noise and unknown but bounded noise, respectively.

Originality/value

To the best knowledge of the authors, this problem of the model parameter identification for aircraft flutter was proposed by their previous work, and they proposed many identification strategies to identify these model parameters. This paper proposes two novel identification strategies and opens a new subject about optimal input signal design for statistical noise and unknown noise, respectively.

Details

Aircraft Engineering and Aerospace Technology, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1748-8842

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Article
Publication date: 4 September 2009

Xiaogang Wang, Naigang Cui and Jifeng Guo

The purpose of this paper is to estimate the relative states between the leader and wingman based on vision‐based relative navigation system using extended information…

Abstract

Purpose

The purpose of this paper is to estimate the relative states between the leader and wingman based on vision‐based relative navigation system using extended information filtering (EIF).

Design/methodology/approach

For a typical leader‐wingman formation case, the relative navigation equations are introduced. Vision‐based navigation system which consists of an optical sensor and a series of specific light sources is used to capture the line‐of‐sight measurement between the two unmanned aerial vehicles (UAVs). Owing to the limitations on the field of view of the optical sensor, not every specific light source would be visible. And the spatial relative position of the two vehicles could also contributes to the diminution of visibility since some of the light sources are likely to be shielded by the frame and wing. Therefore, the EIF can be applied to the vision‐based relative navigation while every specific light source is regarded and processed as an individual information source. It is demonstrated that the information of visual source could be easily extracted by the simple update equation of information filtering.

Findings

The EIF could be used in vision‐based relative navigation system to give an accurate estimation of relative position, velocity and attitude without increasing the amount of calculation or decreasing the estimation accuracy compared to conventional Kalman filtering.

Originality/value

The EIF is first introduced to the vision‐based relative navigation in order to provide relative state between UAVs during formation flight.

Details

Aircraft Engineering and Aerospace Technology, vol. 81 no. 5
Type: Research Article
ISSN: 0002-2667

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Article
Publication date: 3 October 2016

Yongbin Sun, Ning Xian and Haibin Duan

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…

Abstract

Purpose

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).

Design/methodology/approach

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.

Findings

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

Practical implications

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.

Originality/value

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.

Details

Aircraft Engineering and Aerospace Technology, vol. 88 no. 6
Type: Research Article
ISSN: 1748-8842

Keywords

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Article
Publication date: 13 November 2017

Sunan Huang, Swee Huat Rodney Teo, Wenqi Liu and Siarhei Michailovich Dymkou

Cooperative control of a group of unmanned aerial vehicles (UAVs) is an important area of research. The purpose of this paper is to explore multi-UAV control in the…

Abstract

Purpose

Cooperative control of a group of unmanned aerial vehicles (UAVs) is an important area of research. The purpose of this paper is to explore multi-UAV control in the framework of providing surveillance of areas of interest with automatic loss detection and replacement capabilities.

Design/methodology/approach

The research is based on the concept of the multi-agent system. The authors present the framework of the multi-agent and protocol design for monitoring the network of a group of UAVs.

Findings

If one or more UAVs which is conducting a high priority surveillance task is lost, the system can self-arrange for another UAV to replace the lost UAV and continue to execute its task. This research provides an excellent design protocol for UAV loss detection and replacement scheme.

Research limitations/implications

One of the major limitations of this research is that we have only two types of priority levels, high or low. If the priority is more than two levels, for example, high priority 1, high priority 2, or high priority 3, the replacement has not yet been implemented.

Originality/value

This paper contributes to the following two aspects of the scientific knowledge. The first contribution is the design of an agent model which jointly considers system architecture, communication, control logic and target monitoring. The second contribution includes the decentralized and automatic UAV loss detection and replacement algorithm.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 10 no. 4
Type: Research Article
ISSN: 1756-378X

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Article
Publication date: 8 August 2016

Chethan Upendra Chithapuram, Aswani Kumar Cherukuri and Yogananda V. Jeppu

The purpose of this paper is to develop a new guidance scheme for aerial vehicles based on artificial intelligence. The new guidance scheme must be able to intercept…

Abstract

Purpose

The purpose of this paper is to develop a new guidance scheme for aerial vehicles based on artificial intelligence. The new guidance scheme must be able to intercept maneuvering targets with higher probability and precision compared to existing algorithms.

Design/methodology/approach

A simulation setup of the aerial vehicle guidance problem is developed. A model-based machine learning technique known as Q-learning is used to develop a new guidance scheme. Several simulation experiments are conducted to train the new guidance scheme. Orthogonal arrays are used to define the training experiments to achieve faster convergence. A well-known guidance scheme known as proportional navigation guidance (PNG) is used as a base model for training. The new guidance scheme is compared for performance against standard guidance schemes like PNG and augmented proportional navigation guidance schemes in presence of sensor noise and computational delays.

Findings

A new guidance scheme for aerial vehicles is developed using Q-learning technique. This new guidance scheme has better miss distances and probability of intercept compared to standard guidance schemes.

Research limitations/implications

The research uses simulation models to develop the new guidance scheme. The new guidance scheme is also evaluated in the simulation environment. The new guidance scheme performs better than standard existing guidance schemes.

Practical implications

The new guidance scheme can be used in various aerial guidance applications to reach a dynamically moving target in three-dimensional space.

Originality/value

The research paper proposes a completely new guidance scheme based on Q-learning whose performance is better than standard guidance schemes.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 9 no. 3
Type: Research Article
ISSN: 1756-378X

Keywords

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Article
Publication date: 4 June 2021

Gulay Unal

Fault detection, isolation and reconfiguration of the flight control system is an important problem to obtain healthy flight. This paper aims to propose an integrated…

Abstract

Purpose

Fault detection, isolation and reconfiguration of the flight control system is an important problem to obtain healthy flight. This paper aims to propose an integrated approach for aircraft fault-tolerant control.

Design/methodology/approach

The integrated structure includes a Kalman filter to obtain without noise, a full order observer for sensor fault detection, a GOS (generalized observer scheme) for sensor fault isolation and a fuzzy controller to reconfigure of the healthy sensor. This combination is simulated using the state space model of a lateral flight control system in case of disturbance and under sensor fault scenario.

Findings

Using a dedicated observer scheme, the detection and time of sensor fault are correct, but the sensor fault isolation is evaluated incorrectly while the faulty sensor is isolated correctly using GOS. The simulation results show that the suggested approach works affectively for sensor faults with disturbance.

Originality/value

This paper proposes an integrated approach for aircraft fault-tolerant control. Under this framework, three units are designed, one is Kalman filter for filtering and the other is GOS for sensor fault isolation and another is fuzzy logic for reconfiguration. An integrated approach is sensitive to faults that have disturbances. The simulation results show the proposed integrated approach can be used for any linear system.

Details

Aircraft Engineering and Aerospace Technology, vol. 93 no. 4
Type: Research Article
ISSN: 1748-8842

Keywords

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