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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

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. 93 no. 10
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 4 March 2022

Wang Jianhong

The purpose of this paper is to extend the authors’ previous contributions on aircraft flutter model parameters identification. Because closed-loop condition is more…

Abstract

Purpose

The purpose of this paper is to extend the authors’ previous contributions on aircraft flutter model parameters identification. Because closed-loop condition is more widely used in today’s practice, a closed-loop stochastic model of the aircraft flutter test is constructed to model the aircraft flutter process, whose input–output signals are all corrupted by the observed noises. Through using a rational transfer function, the equivalent property between the aircraft flutter model parameters and polynomial coefficients is established, and then the problem of aircraft flutter model parameters identification is turned to one closed-loop identification problem. An iterative identification algorithm is proposed to identify the unknown polynomial coefficients, being benefit for the latter flutter model parameter identification. Furthermore, as the closed-loop output corresponds to the flutter amplitude, so from the point of the minimization with respect to the variance of the closed-loop output, the optimal input signal and optimal feedback controller are all derived to achieve the zero flutter, respectively, for example, the optimal input spectrum and the detailed form for optimal feedback controller.

Design/methodology/approach

First, model parameter identification for aircraft flutter is reviewed as one problem of parameter identification and this aircraft flutter model corresponds to one closed-loop stochastic model, whose input signal and output are corrupted by external noises. Second, for aircraft flutter closed-loop statistical model with statistical noise, an iterative identification algorithm is proposed to identify the unknown model parameters. Third, from the point of minimizing with respect to the variance of the closed-loop output, the optimal input signal and optimal feedback controller are all derived to achieve the zero flutter, respectively, for example, the optimal input spectrum and the detailed form for optimal feedback controller.

Findings

This aircraft flutter model corresponds to one closed-loop stochastic model, whose input signal and output are corrupted by external noises. Then, identification algorithm and optimal input signal design are studied for aircraft flutter model parameter identification with statistical noise, respectively. It means the optimal input signal and optimal feedback controller are useful for the aircraft flutter model parameter identification within the constructed new closed-loop stochastic model.

Originality/value

To the best of the authors’ knowledge, this problem of the model parameter identification for aircraft flutter is proposed by their previous work, and they proposed many identification strategies to identify these model parameters. This paper proposes a new closed-loop stochastic model to construct the aircraft flutter test, and some related topics are considered about this closed-loop identification for aircraft flutter model parameter identification in the framework of closed-loop condition.

Details

Aircraft Engineering and Aerospace Technology, vol. 94 no. 7
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 12 December 2022

Wang Jianhong and Ricardo A. Ramirez-Mendoza

This new paper aims to extend the authors’ previous contributions about open-loop aircraft flutter test to closed-loop aircraft flutter test by virtue of the proposed…

Abstract

Purpose

This new paper aims to extend the authors’ previous contributions about open-loop aircraft flutter test to closed-loop aircraft flutter test by virtue of the proposed direct data–driven strategy. After feeding back the output signal to the input and introducing one feedback controller in the adding feedback loop, two parts, i.e. unknown aircraft flutter model and unknown feedback controller, exist in this closed-loop aircraft flutter system, simultaneously, whose input and output are all corrupted with external noise. Because of the relations between aircraft flutter model parameters and the unknown aircraft model, direct data–driven identification is proposed to identify that aircraft flutter model, then some identification algorithms and their statistical analysis are given through the authors’ own derivations. As the feedback controller can suppress the aircraft flutter or guarantee the flutter response converge to one desired constant value, the direct data–driven control is applied to design that feedback controller only through the observed data sequence directly. Numerical simulation results have demonstrated the efficiency of the proposed direct data–driven strategy. Generally, during our new information age, direct data–driven strategy is widely applied around our living life.

Design/methodology/approach

First, consider one more complex closed loop stochastic aircraft flutter model, whose input–output are all corrupted with external noise. Second, for the identification problem of closed-loop aircraft flutter model parameters, new identification algorithm and some considerations are given to the corresponding direct data–driven identification. Third, to design that feedback controller, existing in that closed-loop aircraft flutter model, direct data–driven control is proposed to design the feedback controller, which suppresses the flutter response actively.

Findings

A novel direct data–driven strategy is proposed to achieve the dual missions, i.e. identification and control for closed-loop aircraft flutter test. First, direct data–driven identification is applied to identify that unknown aircraft flutter model being related with aircraft flutter model parameters identification. Second, direct data–driven control is proposed to design that feedback controller.

Originality/value

To the best of the authors’ knowledge, this new paper extends the authors’ previous contributions about open-loop aircraft flutter test to closed-loop aircraft flutter test by virtue of the proposed direct data–driven strategy. Consider the identification problem of aircraft flutter model parameters within the presented closed loop environment, direct data–driven identification algorithm is proposed to achieve the identification goal. Direct data–driven control is proposed to design the feedback controller, i.e. only using the observed data to design the feedback controller.

Details

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

Keywords

Article
Publication date: 5 July 2021

Wang Jianhong

The purpose of this paper is to derive the output predictor for a stationary normal process with rational spectral density and linear stochastic discrete-time state-space…

Abstract

Purpose

The purpose of this paper is to derive the output predictor for a stationary normal process with rational spectral density and linear stochastic discrete-time state-space model, respectively, as the output predictor is very important in model predictive control. The derivations are only dependent on matrix operations. Based on the output predictor, one quadratic programming problem is constructed to achieve the goal of subspace predictive control. Then an improved ellipsoid optimization algorithm is proposed to solve the optimal control input and the complexity analysis of this improved ellipsoid optimization algorithm is also given to complete the previous work. Finally, by the example of the helicopter, the efficiency of the proposed control strategy can be easily realized.

Design/methodology/approach

First, a stationary normal process with rational spectral density and one stochastic discrete-time state-space model is described. Second, the output predictors for these two forms are derived, respectively, and the derivation processes are dependent on the Diophantine equation and some basic matrix operations. Third, after inserting these two output predictors into the cost function of predictive control, the control input can be solved by using the improved ellipsoid optimization algorithm and the complexity analysis corresponding to this improved ellipsoid optimization algorithm is also provided.

Findings

Subspace predictive control can not only enable automatically tune the parameters in predictive control but also avoids many steps in classical linear Gaussian control. It means that subspace predictive control is independent of any prior knowledge of the controller. An improved ellipsoid optimization algorithm is used to solve the optimal control input and the complexity analysis of this algorithm is also given.

Originality/value

To the best knowledge of the authors, this is the first attempt at deriving the output predictors for stationary normal processes with rational spectral density and one stochastic discrete-time state-space model. Then, the derivation processes are dependent on the Diophantine equation and some basic matrix operations. The complexity analysis corresponding to this improved ellipsoid optimization algorithm is analyzed.

Details

Aircraft Engineering and Aerospace Technology, vol. 93 no. 5
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 13 June 2022

Wang Jianhong and Ricardo A. Ramirez-Mendoza

The purpose of this paper extends the authors’ previous contributions on aircraft system identification, such as open loop identification or closed loop identification, to…

Abstract

Purpose

The purpose of this paper extends the authors’ previous contributions on aircraft system identification, such as open loop identification or closed loop identification, to cascade system identification. Because the cascade system is one special network system, existing in lots of practical engineers, more unknown systems are needed to identify simultaneously within the statistical environment with the probabilistic noises. Consider this problem of cascade system identification, prediction error method is proposed to identify three unknown systems, which are parameterized by three unknown parameter vectors. Then the cascade system identification is transferred as one parameter identification problem, being solved by the online subgradient descent algorithm. Furthermore, the nonparametric estimation is proposed to consider the general case without any parameterized process. To make up the identification mission, model validation process is given to show the asymptotic interval of the identified parameter. Finally, simulation example confirms the proposed theoretical results.

Design/methodology/approach

Firstly, aircraft system identification is reviewed through the understanding about system identification and advances in control theory, then cascade system identification is introduced to be one special network system. Secondly, for the problem of cascade system identification, prediction error method and online subgradient decent algorithm are combined together to identify the cascade system with the parameterized systems. Thirdly from the point of more general completeness, another way is proposed to identify the nonparametric estimation, then model validation process is added to complete the whole identification mission.

Findings

This cascade system corresponds to one network system, existing in lots of practice, such as aircraft, ship and robot, so it is necessary to identify this cascade system, paving a way for latter network system identification. Parametric and nonparametric estimations are all studied within the statistical environment. Then research on bounded noise is an ongoing work.

Originality/value

To the best of the authors’ knowledge, research on aircraft system identification only concern on open loop and closed loop system identification, no any identification results about network system identification. This paper considers cascade system identification, being one special case on network system identification, so this paper paves a basic way for latter more advanced system identification and control theory.

Details

Aircraft Engineering and Aerospace Technology, vol. 95 no. 1
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 26 May 2020

Changhai Lin, Zhengyu Song, Sifeng Liu, Yingjie Yang and Jeffrey Forrest

The purpose of this paper is to analyze the mechanism and filter efficacy of accumulation generation operator (AGO)/inverse accumulation generation operator (IAGO) in the…

Abstract

Purpose

The purpose of this paper is to analyze the mechanism and filter efficacy of accumulation generation operator (AGO)/inverse accumulation generation operator (IAGO) in the frequency domain.

Design/methodology/approach

The AGO/IAGO in time domain will be transferred to the frequency domain by the Fourier transform. Based on the consistency of the mathematical expressions of the AGO/IAGO in the gray system and the digital filter in digital signal processing, the equivalent filter model of the AGO/IAGO is established. The unique methods in digital signal processing systems “spectrum analysis” of AGO/IAGO are carried out in the frequency domain.

Findings

Through the theoretical study and practical example, benefit of spectrum analysis is explained, and the mechanism and filter efficacy of AGO/IAGO are quantitatively analyzed. The study indicated that the AGO is particularly suitable to act on the system's behavior time series in which the long period parts is the main factor. The acted sequence has good effect of noise immunity.

Practical implications

The AGO/IAGO has a wonderful effect on the processing of some statistical data, e.g. most of the statistical data related to economic growth, crop production, climate and atmospheric changes are mainly affected by long period factors (i.e. low-frequency data), and most of the disturbances are short-period factors (high-frequency data). After processing by the 1-AGO, its high frequency content is suppressed, and its low frequency content is amplified. In terms of information theory, this two-way effect improves the signal-to-noise ratio greatly and reduces the proportion of noise/interference in the new sequence. Based on 1-AGO acting, the information mining and extrapolation prediction will have a good effect.

Originality/value

The authors find that 1-AGO has a wonderful effect on the processing of data sequence. When the 1-AGO acts on a data sequence X, its low-pass filtering effect will benefit the information fluctuations removing and high-frequency noise/interference reduction, so the data shows a clear exponential change trends. However, it is not suitable for excessive use because its equivalent filter has poles at the non-periodic content. But, because of pol effect at zero frequency, the 1-AGO will greatly amplify the low-frequency information parts and suppress the high-frequency parts in the information at the same time.

Details

Grey Systems: Theory and Application, vol. 11 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 30 August 2022

Xu Wang, Xin Feng and Kaixuan Guo

Quantitative analysis of existing literature is conducted to compare the textual features of ethics education in science and technology under the broad theme of ethics in…

Abstract

Purpose

Quantitative analysis of existing literature is conducted to compare the textual features of ethics education in science and technology under the broad theme of ethics in science and technology. On this basis, the authors reveal the research hotspots and topic evolution in this field, and propose development suggestions in conjunction with the 5W theory.

Design/methodology/approach

In this paper, the authors visualize the graph and quantify the indicators in four aspects: time series, institutional collaboration, author co-authorship, and research hotspots.

Findings

Compared to ethics of science and technology, the research results in the field of ethics of science and technology education are limited. There is still room for improvement in the low density of cooperation between authors and institutions. The research themes are focused on theoretical discussions and countermeasure research. At present, the reform of ethics of science and technology is still in its infancy and has not yet formed a perfect system for education and personnel training. It is necessary for research on the ethical theory of technology to provide theoretical support.

Originality/value

In the context of sustainable development strategies, it is beneficial to explore the path of pedagogical optimization of ethics of science and technology in this study. This includes the maintenance of a good research environment and the realization of a healthy development in the field of science and technology.

Details

Library Hi Tech, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0737-8831

Keywords

Article
Publication date: 23 August 2018

Jianhong Luo, Xuwei Pan, Shixiong Wang and Yujing Huang

Delivering messages and information to potentially interested users is one of the distinguishing applications of online enterprise social network (ESN). The purpose of…

3642

Abstract

Purpose

Delivering messages and information to potentially interested users is one of the distinguishing applications of online enterprise social network (ESN). The purpose of this paper is to provide insights to better understand the repost preferences of users and provide personalized information service in enterprise social media marketing.

Design/methodology/approach

It is accomplished by constructing a target audience identification framework. Repost preference latent Dirichlet allocation (RPLDA) topic model topic model is proposed to understand the mass user online repost preferences toward different contents. A topic-oriented preference metric is proposed to measure the preference degree of individual users. And the function of reposting forecasting is formulated to identify target audience.

Findings

The empirical research shows the following: a total of 20 percent of the repost users in ESN represent the key active users who are particularly interested in the latent topic of messages in ESN and fits Pareto distribution; and the target audience identification framework can successfully identify different target key users for messages with different latent topics.

Practical implications

The findings should motivate marketing managers to improve enterprise brand by identifying key target audience in ESN and marketing in a way that truthfully reflects personalized preferences.

Originality/value

This study runs counter to most current business practices, which tend to use simple popularity to seek important users. Adaptively and dynamically identifying target audience appears to have considerable potential, especially in the rapidly growing area of enterprise social media information service.

Details

Industrial Management & Data Systems, vol. 119 no. 1
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 25 August 2022

Yuning Wu, Ivan Sun, Tzu-Ying Lo and Jianhong Liu

This paper comparatively assesses the connections between individual demographic traits, occupational characteristics, and organizational factors and officers' attitudes…

Abstract

Purpose

This paper comparatively assesses the connections between individual demographic traits, occupational characteristics, and organizational factors and officers' attitudes toward important groups in China and Taiwan.

Design/methodology/approach

Survey data used in this study were collected from 722 police officers from mainland China and 531 officers from Taiwan. Multivariate regression analyses were conducted to assess the correlates of police attitudes toward peers, supervisors, and citizens.

Findings

The Chinese and Taiwanese officers do not differ in their trust in peers, but the Chinese officers hold significantly more positive views on the trustworthiness of supervisors and citizens compared to the Taiwanese officers. Supervisor justice and organizational identification are significant predictors of officers' attitudes toward all three groups in both countries.

Research limitations/implications

A major limitation revolves around the inability to test and explain exactly why findings from the two groups vary in their ways. Future research should include specific social, political, and cultural predictors.

Originality/value

This study represents one of the few studies that compare police attitudes toward important groups of peers, supervisors, and citizens across nations/cultures.

Details

Policing: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1363-951X

Keywords

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