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1 – 10 of over 15000The 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…
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.
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Lei Wang, Xiaojun Wang and Xiao Li
– The purpose of this paper is to focus on the influences of the uncertain dynamic responses on the reconstruction of loads.
Abstract
Purpose
The purpose of this paper is to focus on the influences of the uncertain dynamic responses on the reconstruction of loads.
Design/methodology/approach
Based on the assumption of unknown-but-bounded (UBB) noise, a time-domain approach to estimate the uncertain time-dependent external loads is presented by combining the inverse system method in modern control theory and interval analysis in interval mathematics. Inspired by the concept of set membership identification in control theory, an interval analysis model of external loads time history, which is indeed a region or feasible set containing all possible loads being consistent with the bounded structural acceleration responses is established and further solved by two interval algorithms.
Findings
Unlike traditional loads identification methods which only give a point estimation, an interval estimation of external loads time history, which is a region containing all the possible loads being consistent with the uncertain structural responses, is determined. The correlation characteristics among the responses of acceleration, velocity, and displacement are also discussed in consideration of the UBB uncertainty.
Originality/value
For one hand, the solution of the inverse problem in original system is transformed to the solution of the direct problem in inverse system; for another, the authors deal with the uncertainty by use of interval analysis method, and the identified interval process, which contains any possible external loads time history being consistent with the bounded structural responses can be approximately obtained.
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The purpose of this paper is to probe the recursive identification of piecewise affine Hammerstein models directly by using input-output data. To explain the identification…
Abstract
Purpose
The purpose of this paper is to probe the recursive identification of piecewise affine Hammerstein models directly by using input-output data. To explain the identification process of a parametric piecewise affine nonlinear function, the authors prove that the inverse function corresponding to the given piecewise affine nonlinear function is also an equivalent piecewise affine form. Based on this equivalent property, during the detailed identification process with respect to piecewise affine function and linear dynamical system, three recursive least squares methods are proposed to identify those unknown parameters under the probabilistic description or bounded property of noise.
Design/methodology/approach
First, the basic recursive least squares method is used to identify those unknown parameters under the probabilistic description of noise. Second, multi-innovation recursive least squares method is proposed to improve the efficiency lacked in basic recursive least squares method. Third, to relax the strict probabilistic description on noise, the authors provide a projection algorithm with a dead zone in the presence of bounded noise and analyze its two properties.
Findings
Based on complex mathematical derivation, the inverse function of a given piecewise affine nonlinear function is also an equivalent piecewise affine form. As the least squares method is suited under one condition that the considered noise may be a zero mean random signal, a projection algorithm with a dead zone in the presence of bounded noise can enhance the robustness in the parameter update equation.
Originality/value
To the best knowledge of the authors, this is the first attempt at identifying piecewise affine Hammerstein models, which combine a piecewise affine function and a linear dynamical system. In the presence of bounded noise, the modified recursive least squares methods are efficient in identifying two kinds of unknown parameters, so that the common set membership method can be replaced by the proposed methods.
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Jie Chu, Junhong Li, Yizhe Jiang, Weicheng Song and Tiancheng Zong
The Wiener-Hammerstein nonlinear system is made up of two dynamic linear subsystems in series with a static nonlinear subsystem, and it is widely used in electrical, mechanical…
Abstract
Purpose
The Wiener-Hammerstein nonlinear system is made up of two dynamic linear subsystems in series with a static nonlinear subsystem, and it is widely used in electrical, mechanical, aerospace and other fields. This paper considers the parameter estimation of the Wiener-Hammerstein output error moving average (OEMA) system.
Design/methodology/approach
The idea of multi-population and parameter self-adaptive identification is introduced, and a multi-population self-adaptive differential evolution (MPSADE) algorithm is proposed. In order to confirm the feasibility of the above method, the differential evolution (DE), the self-adaptive differential evolution (SADE), the MPSADE and the gradient iterative (GI) algorithms are derived to identify the Wiener-Hammerstein OEMA system, respectively.
Findings
From the simulation results, the authors find that the estimation errors under the four algorithms stabilize after 120, 30, 20 and 300 iterations, respectively, and the estimation errors of the four algorithms converge to 5.0%, 3.6%, 2.7% and 7.3%, which show that all four algorithms can identify the Wiener-Hammerstein OEMA system.
Originality/value
Compared with DE, SADE and GI algorithm, the MPSADE algorithm not only has higher parameter estimation accuracy but also has a faster convergence speed. Finally, the input–output relationship of laser welding system is described and identified by the MPSADE algorithm. The simulation results show that the MPSADE algorithm can effectively identify parameters of the laser welding system.
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Kimberley D. Preiksaitis and Peter A. Dacin
This study aims to examine how brands attempt to extend their customer set not through the typical route of adding brands, but through the strategic extension or enlargement of…
Abstract
Purpose
This study aims to examine how brands attempt to extend their customer set not through the typical route of adding brands, but through the strategic extension or enlargement of their target customer set. Building on theories from both reference group perceptions and brand identification, this research explores the impact of strategic customer extensions on current target market consumers.
Design/methodology/approach
Two scenario-based experiments explore strategic customer extensions for a packaged goods brand and a well-known retail brand. The analysis involves both analysis of variance and SEM methods.
Findings
Current target market consumers’ evaluations of strategic customer extensions are informed by reference group perceptions relating to the proposed customer extension. When current target market consumers perceive strategic customer extensions as potentially attracting a dissociative reference group, consumers have weaker evaluations and brand identification measures and, subsequently, weaker future intentions towards the brand.
Originality/value
The brand identification literature is augmented by incorporating theories from the reference group literature to demonstrate how to reference group perceptions drive a current target market consumers’ evaluations of strategic customer extensions to affect the strength of the identification that current target market consumers have with a brand. Brand identification is also demonstrated as mediator customer evaluations and subsequent intentions towards the brand.
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This paper examines social influence in collective task settings using the Berger, Fisek, Norman and Zelditch's graph-theoretic method. The work examines in-group membership in…
Abstract
This paper examines social influence in collective task settings using the Berger, Fisek, Norman and Zelditch's graph-theoretic method. The work examines in-group membership in task settings, and models contexts where both status processes and group membership are salient. At the core of these models is a theoretical concept called a group status typification state, defined as an abstract understanding that participants hold of the type of person who would be a good source of information. This paper builds upon recent theory and research and may serve as an initial step toward integration of Status Characteristics Theory and Social Identity Theory.
Utino Worabo Woju and A.S. Balu
The aim of this paper is mainly to handle the fuzzy uncertainties present in structures appropriately. In general, uncertainties of variables are classified as aleatory and…
Abstract
Purpose
The aim of this paper is mainly to handle the fuzzy uncertainties present in structures appropriately. In general, uncertainties of variables are classified as aleatory and epistemic. The different sources of uncertainties in reinforced concrete structures include the randomness, mathematical models, physical models, environmental factors and gross errors. The effects of imprecise data in reinforced concrete structures are studied here by using fuzzy concepts. The aim of this paper is mainly to handle the uncertainties of variables with unclear boundaries.
Design/methodology/approach
To achieve the intended objective, the reinforced concrete beam subjected to flexure and shear was designed as per Euro Code (EC2). Then, different design parameters such as corrosion parameters, material properties and empirical expressions of time-dependent material properties were identified through a thorough literature review.
Findings
The fuzziness of variables was identified, and their membership functions were generated by using the heuristic method and drawn by MATLAB R2018a software. In addition to the identification of fuzziness of variables, the study further extended to design optimization of reinforced concrete structure by using fuzzy relation and fuzzy composition.
Originality/value
In the design codes of the concrete structure, the concrete grades such as C16/20, C20/25, C25/30, C30/37 and so on are provided and being adopted for design in which the intermediate grades are not considered, but using fuzzy concepts the intermediate grades of concrete can be recognized by their respective degree of membership. In the design of reinforced concrete structure using fuzzy relation and composition methods, the optimum design is considered when the degree of membership tends to unity. In addition to design optimization, the level of structural performance evaluation can also be carried out by using fuzzy concepts.
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Patricia Garcia-Prieto, Diane M. Mackie, Veronique Tran and Eliot R. Smith
In this chapter we apply intergroup emotion theory (IET; Mackie, Devos, & Smith, 2000) to reflect on the conditions under which individuals may experience intergroup emotions in…
Abstract
In this chapter we apply intergroup emotion theory (IET; Mackie, Devos, & Smith, 2000) to reflect on the conditions under which individuals may experience intergroup emotions in workgroups, and to explore some possible consequences of those emotions. First, we briefly outline IET and describe the psychological mechanisms underlying intergroup emotion with a particular emphasis on the role of social identification. Second, we describe some of the antecedents of shared and varied social identifications in workgroups, which may in turn elicit shared or varied intergroup emotions in workgroups. Finally, we consider potential consequences for both relationship and task outcomes such as organizational citizenship behavior, workgroup cohesion, relationship and task conflict, issue interpretation, and information sharing.
Jodie Kleinschafer, David Dowell and Mark Morrison
The purpose of this paper is to develop insight regarding art gallery members' identification with their galleries through the use of segmentation. The antecedents of a member's…
Abstract
Purpose
The purpose of this paper is to develop insight regarding art gallery members' identification with their galleries through the use of segmentation. The antecedents of a member's identification and subsequent involvement with the gallery are explored. Within the four regional art galleries analysed, the authors identify three different segments within the membership groups which illustrate the ways in which gallery members, who identify positively with their gallery, contribute to the organisation through behaviours such as the donation of time and money.
Design/methodology/approach
A mixed methods approach was used, including 11 in‐depth interviews with gallery staff and members and a survey (n=433) of gallery members. The in‐depth interviews were interpreted using content analysis and thematic analysis. The survey results were analysed using exploratory factor analysis and cluster analysis.
Findings
The paper's findings suggest that gallery members can be differentiated in terms of the way that they contribute to their art gallery. Three types were identified: promoters, donors and committee members. A number of constructs were used to distinguish between each of the segments, including: member identification, satisfaction, prestige, visibility, contact quality and domain involvement from the current arts marketing literature. Four other constructs which emerged from the qualitative research were also used to profile the clusters: self‐enhancement, organisational culture, social responsibility and elitism which emerged from the qualitative research.
Research limitations/implications
Profiling different segments in the market (membership) using sociodemographics, attitudes and donating behaviours allows marketers and managers to more effectively target the segments who can positively contribute to the organisation. Moreover it provides a greater understanding of the membership base and how various members are engaging with their institution. Current methods of marketing are becoming less ideal to obtain marketing objectives, with diminishing returns to scale on marketing programmes an issue.
Practical implications
An understanding of the differences between each of these member types will allow galleries to more efficiently use their finite resources. By tailoring offerings to each of the different segments galleries can maximise the value of their membership base. Further, the use of segmentation enables gallery managers to identify segments where members may be less or not engaged and its causes and potential solutions.
Social implications
Many non‐profit organisations with a membership base, such as the art galleries sampled in this research, rely on the contribution of their membership to survive. Therefore understanding the relationship between the institution and the membership is important.
Originality/value
The paper is unique in the application of segmentation analysis to examine gallery members. It also furthers the current understanding of identification and its role in the relationship between organisation members and their behaviour as members. That is the role of identification in relationship marketing.
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