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The purpose of this paper is to achieve fault reconstruction for reaction wheels in spacecraft attitude control systems (ACSs) subject to space disturbance torques.

Considering the influence of rotating reaction wheels on spacecraft attitude dynamics, a novel non-linear learning observer is suggested to robustly reconstruct the loss of reaction wheel effectiveness faults, and its stability is proven using Lyapunov’s indirect method. Further, an extension of the proposed approach to bias faults reconstruction for reaction wheels in spacecraft ACSs is performed.

The numerical example and simulation demonstrate the effectiveness of the proposed fault-reconstructing methods.

This paper includes implications for the development of reliability and survivability of on-orbit spacecrafts.

This paper proposes a novel non-linear learning observer-based reaction wheels fault reconstruction for spacecraft ACSs.

Gives a bibliographical review of the error estimates and adaptive finite element methods from the theoretical as well as the application point of view. The bibliography at the end contains 2,177 references to papers, conference proceedings and theses/dissertations dealing with the subjects that were published in 1990‐2000.

The purpose of this paper is to describe how a generalized single-system-single-solve (GS4-1) computational framework, previously developed for linear first order transient systems, can be properly extended for use in nonlinear counterparts, with particular applications to time dependent Burgers’ equation, which is well-known to serve as a simplified model of fluid dynamics, for illustrations of the essential concepts.

The framework permits, for a very general family of time integrators where traditional methods are a subset, much needed desirable features including second order time accuracy, robustness and unconditional stability, zero-order overshoot behavior, and additionally, a selective control of high frequency damping for both the primary variable and its time derivative. The latter, which is a new, key desirable feature not available in past/existing methods to-date, allows for different amounts of high frequency damping for both the primary variable and its time derivative to ensure physically accurate solutions of these variables. This is in contrast to having only limited control of these numerical dampings, often indiscriminately, as in some past developments which can lead to numerical instabilities in the time derivative variable. The extension of the framework to nonlinear problems, as described in this paper, is achieved via the use of a normalized time weighted residual approach, which naturally allows the time discretization of the transient nonlinear systems as being the natural extensions of the linear systems.

The primary aim is also to demonstrate the advantage of the selective control feature inherit in the present numerical methodologies for these nonlinear first order transient systems as in the linear counterparts.

The authors wish to tackle the challenges to further enable extensions to nonlinear first order transient systems that frequently arise in fluid dynamics problems; this is the focus of this paper. The primary wish is to demonstrate the ability of the GS4-1 framework for nonlinear first order transient systems as seen in the linear transient counterparts; while on one hand the authors show that an equal amount of high frequency damping (i.e. ρ _∞ = ρ _∞ s) leads to non-physical instability in the time derivative variable for a minimal damping required to obtain acceptable solution of the primary variable, on the other hand, the authors particularly demonstrate how this instability can be easily tuned off via the selective control feature (i.e. ρ _∞ ≠ ρ _∞ s) offered by the developed framework; thereby, demonstrating its robustness and superiority.

This paper aims to adopt the complexity theory (CT) as a frame of reference to analyze leadership action within a military organization. Through the CT framework, it considers a military organization as a complex adaptive system (CAS), which evolves and adapts to the environment to survive, similarly to a living organism. This case study identifies complex dynamics, which are proper to CAS and it proposes avenues to harness them to increase organizational performance. Ultimately, this paper provides insights on how a CT framework may be used in describing and understanding an effective leadership action and grant it with mechanisms to measure its effectiveness.

This paper rests on a single case study, which examines a leadership action in a military organization. Capitalizing on privileged access to top managers of an Air Force’s Major Command, the author carried out tailored surveys aimed at identifying organizational leadership effectiveness.

Based on these data, the study provides qualitative evidence that suggests a relevant relationship between CT-based leadership action and organizational effectiveness.

The CT-based leadership approach challenges the paradigm of ordered, hierarchical organizational design by proposing a more flexible, networked approach in relation to organizational effectiveness. The complexity-based approach to leadership proposed in this paper suggests an adaptive leadership model that better corresponds to complex human organizations, and helps leaders identify more effective management solutions.

This paper aims to devise a robust controller for the non-linear aircraft model using output feedback control topology in the presence of uncertain aerodynamic parameters.

Feedback linearization-based state feedback (SFB) controller is considered along with a robust outer loop control which is designed using Lyapunov’s second method. A high-gain observer (HGO) in accordance with the separation principle is used to implement the output feedback (OFB) control scheme. The robustness of the controller and observer is assessed by introducing uncertain aerodynamics coefficients in the dynamic model. The proposed scheme is validated using MATLAB/SIMULINK.

The efficacy of the proposed scheme is authenticated with the simulation results which show that HGO-based OFB control achieves the SFB control performance for a small value of the high-gain parameter in the presence of uncertain aerodynamic parameters.

A HGO for the non-linear model of aircraft with uncertain parameters is a novel contribution which could be further used for the unmanned aerial vehicles autopilot, flight trajectory tracking and path following.

Many engineering structures exhibit loss of stability under static and dynamic loading. Due to the significance of these phenomena in engineering design this topic has attracted considerable attention during the last decades. In recent years much effort has been made to devise algorithms within finite element analysis to investigate the static stability behaviour of structures. With these methods stable and unstable paths can be traced, and limit or bifurcation points can be computed efficiently. The associated arc‐length or branch‐switching procedures are today standard tools in existing finite element codes.

States that the homo economicus abstraction remains dominant in economics, despite a range of criticisms of its use over the years. Many institutionalists, post‐Keynesians, neo‐Austrians and social economists have insisted that economic analysis must be conducted in an explicit historical context, where the difficulties which economic decision‐makers face, because of time irreversibility, structural change and fundamental uncertainty, are taken into account, as well as non‐economic influences on economic behaviour. Understandably, there has been a reluctance to construct a competing abstraction with formal properties which are comparable to those of the homo economicus construct. It is argued in this paper that the development of an alternative behavioural abstraction constitutes an important goal, both in terms of clarifying the limitations of homo economicus and providing an analytical basis upon which investigations of economic behaviour in historical time can be built.

This paper describes a number of models used in bankruptcy studies to date. They arise from two basic model designs used in studies of financial distress: cross-sectional studies that compare healthy and distressed firms, and time-series formulations that study the path to failure of (usually) distressed firms only. These two designs inherently foster different research objectives. Different instances of the most recent work taken from each of the above research groups, broadly categorized by design, are described here including new work by this author. It is argued that those that investigate the distress continuum with predominantly explanatory objectives are superior on a number of criteria to the studies that follow what is essentially a case-control structure and espouse prediction as their objective.