3,098 research outputs found

    Robust nonlinear control of vectored thrust aircraft

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    An interdisciplinary program in robust control for nonlinear systems with applications to a variety of engineering problems is outlined. Major emphasis will be placed on flight control, with both experimental and analytical studies. This program builds on recent new results in control theory for stability, stabilization, robust stability, robust performance, synthesis, and model reduction in a unified framework using Linear Fractional Transformations (LFT's), Linear Matrix Inequalities (LMI's), and the structured singular value micron. Most of these new advances have been accomplished by the Caltech controls group independently or in collaboration with researchers in other institutions. These recent results offer a new and remarkably unified framework for all aspects of robust control, but what is particularly important for this program is that they also have important implications for system identification and control of nonlinear systems. This combines well with Caltech's expertise in nonlinear control theory, both in geometric methods and methods for systems with constraints and saturations

    Towards Gradient-Based Design Optimization of Flexible Transport Aircraft with Flutter Constraints

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    Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140443/1/6.2014-2726.pd

    A Comparison of Metallic, Composite and Nanocomposite Optimal Transonic Transport Wings

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    Current and future composite material technologies have the potential to greatly improve the performance of large transport aircraft. However, the coupling between aerodynamics and structures makes it challenging to design optimal flexible wings, and the transonic flight regime requires high fidelity computational models. We address these challenges by solving a series of high-fidelity aerostructural optimization problems that explore the design space for the wing of a large transport aircraft. We consider three different materials: aluminum, carbon-fiber reinforced composites and an hypothetical composite based on carbon nanotubes. The design variables consist of both aerodynamic shape (including span), structural sizing, and ply angle fractions in the case of composites. Pareto fronts with respect to structural weight and fuel burn are generated. The wing performance in each case is optimized subject to stress and buckling constraints. We found that composite wings consistently resulted in lower fuel burn and lower structural weight, and that the carbon nanotube composite did not yield the increase in performance one would expect from a material with such outstanding properties. This indicates that there might be diminishing returns when it comes to the application of advanced materials to wing design, requiring further investigation

    Review of trends and targets of complex systems for power system optimization

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    Optimization systems (OSs) allow operators of electrical power systems (PS) to optimally operate PSs and to also create optimal PS development plans. The inclusion of OSs in the PS is a big trend nowadays, and the demand for PS optimization tools and PS-OSs experts is growing. The aim of this review is to define the current dynamics and trends in PS optimization research and to present several papers that clearly and comprehensively describe PS OSs with characteristics corresponding to the identified current main trends in this research area. The current dynamics and trends of the research area were defined on the basis of the results of an analysis of the database of 255 PS-OS-presenting papers published from December 2015 to July 2019. Eleven main characteristics of the current PS OSs were identified. The results of the statistical analyses give four characteristics of PS OSs which are currently the most frequently presented in research papers: OSs for minimizing the price of electricity/OSs reducing PS operation costs, OSs for optimizing the operation of renewable energy sources, OSs for regulating the power consumption during the optimization process, and OSs for regulating the energy storage systems operation during the optimization process. Finally, individual identified characteristics of the current PS OSs are briefly described. In the analysis, all PS OSs presented in the observed time period were analyzed regardless of the part of the PS for which the operation was optimized by the PS OS, the voltage level of the optimized PS part, or the optimization goal of the PS OS.Web of Science135art. no. 107

    Aeroelastic control and estimation with a minimal nonlinear modal description

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    Modal-based, nonlinear Moving Horizon Estimation (MHE) and Model Predictive Control(MPC) strategies for very flexible aeroelastic systems are presented. They are underpinned by an aeroelastic model built from a 1D intrinsic (based on strains and velocities) description of geometrically-nonlinear beams and an unsteady Vortex Lattice aerodynamic model. Construction of a nonlinear, modal-based, reduced order model of the aeroelastic system, employing a state-space realisation of the linearised aerodynamics around an arbitrary reference point, allows us to capture the main nonlinear geometrical couplings at a very low computational cost. Embedding this model in both MHE and MPC strategies, which solve the system continuous-time adjoints efficiently to compute sensitivities, lays the foundations for real-time estimation and control of highly flexible aeroelastic systems. Finally, the performance and versatility of the framework operating in the nonlinear regime is demonstrated on two very flexible wing models, with notably different dynamics, and on two different control setups: a gust-load alleviation problem on a very high aspect ratio wing with slower dynamics, which involves substantial deflections; and flutter suppression on a flexible wing with significantly faster dynamics, where an unconventional nonlinear stabilisation mechanism is unveiled

    SHAPA: An interactive software tool for protocol analysis applied to aircrew communications and workload

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    As modern transport environments become increasingly complex, issues such as crew communication, interaction with automation, and workload management have become crucial. Much research is being focused on holistic aspects of social and cognitive behavior, such as the strategies used to handle workload, the flow of information, the scheduling of tasks, the verbal and non-verbal interactions between crew members. Traditional laboratory performance measures no longer sufficiently meet the needs of researchers addressing these issues. However observational techniques are better equipped to capture the type of data needed and to build models of the requisite level of sophistication. Presented here is SHAPA, an interactive software tool for performing both verbal and non-verbal protocol analysis. It has been developed with the idea of affording the researchers the closest possible degree of engagement with protocol data. The researcher can configure SHAPA to encode protocols using any theoretical framework or encoding vocabulary that is desired. SHAPA allows protocol analysis to be performed at any level of analysis, and it supplies a wide variety of tools for data aggregation, manipulation. The output generated by SHAPA can be used alone or in combination with other performance variables to get a rich picture of the influences on sequences of verbal or nonverbal behavior

    Design Optimization of Flexible Aircraft Wings Using Tow-steered Composites

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    In the last 30 years since their introduction into aerospace applications, composites have become increasingly used, making up as much as 50% of modern aircraft by weight. Considering this fact, it is surprising that most aircraft today are only scratching the surface of the true potential of composite technology with traditional uniaxial fibers. With the introduction of automatic fiber placing machines, the fiber direction in laminae is now allowed to be steered spatially throughout each layer. This process is known as composite tow steering and has been shown to have improved performance over its uniaxial fiber counterpart with no additional weight penalty. With modern aircraft moving toward larger and more flexible wing designs, it is reasonable to expect that a tow-steered composite wing structure can be tailored to outperform its unsteered counterpart. However, given the highly coupled nature of the aerodynamics and structural response of the problem it is not obvious nor intuitive to find the composite fiber pattern that would yield an optimal result. High-fidelity aerostructural solvers have been proven effective for accurately capturing the trade-offs between relevant design disciplines for such aircraft. Such solvers allow for the performance of tow-steered wing structures to be analyzed in great detail. By complementing these solvers with gradient-based numerical optimization, high dimensional design spaces can be explored relatively efficiently. Such methods make it possible to quantify the maximum benefits offered by tow-steered wing structures. In this thesis, a number of aerostructural optimizations are performed to compare the performance of aluminum, conventional composite and tow-steered composite wing designs. For these studies, a set of benchmark aeroelastic aircraft models are developed based on the NASA Common Research Model. A design parameterization scheme, constitutive model, and relevant manufacturing constraints are then developed for tow-steered structures. A fuel burn minimization is then performed for a tow-steered and conventional composite wing design. When applied to a Boeing-777-type aircraft wing, tow steering is found to offer improvements of up to 2.4% in fuel savings and 24% in wing weight under the limited set of design constraints, relative to the optimized conventional composite design. This improvement was found to be due to a combination of improved passive aeroelastic tailoring and local strength tailoring in high-stressed regions in the tow-steered structure. For a higher aspect ratio wing design improvements of up to 1.5% and 14% in fuel savings and wing weight are found. Finally, the trade-off between structural weight and fuel burn performance is explored through a Pareto front study. This study compares the performance of an aluminum, conventional and tow-steered composite wing. In this study, it is found that when wing planform is free to vary, tow-steering offers improvements of up to 1.5% in fuel savings for a fuel-burn-optimized design and 1.6% in total aircraft weight savings for the structural-weight-optimized.PHDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145830/1/timryanb_1.pd

    Architecture and Information Requirements to Assess and Predict Flight Safety Risks During Highly Autonomous Urban Flight Operations

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    As aviation adopts new and increasingly complex operational paradigms, vehicle types, and technologies to broaden airspace capability and efficiency, maintaining a safe system will require recognition and timely mitigation of new safety issues as they emerge and before significant consequences occur. A shift toward a more predictive risk mitigation capability becomes critical to meet this challenge. In-time safety assurance comprises monitoring, assessment, and mitigation functions that proactively reduce risk in complex operational environments where the interplay of hazards may not be known (and therefore not accounted for) during design. These functions can also help to understand and predict emergent effects caused by the increased use of automation or autonomous functions that may exhibit unexpected non-deterministic behaviors. The envisioned monitoring and assessment functions can look for precursors, anomalies, and trends (PATs) by applying model-based and data-driven methods. Outputs would then drive downstream mitigation(s) if needed to reduce risk. These mitigations may be accomplished using traditional design revision processes or via operational (and sometimes automated) mechanisms. The latter refers to the in-time aspect of the system concept. This report comprises architecture and information requirements and considerations toward enabling such a capability within the domain of low altitude highly autonomous urban flight operations. This domain may span, for example, public-use surveillance missions flown by small unmanned aircraft (e.g., infrastructure inspection, facility management, emergency response, law enforcement, and/or security) to transportation missions flown by larger aircraft that may carry passengers or deliver products. Caveat: Any stated requirements in this report should be considered initial requirements that are intended to drive research and development (R&D). These initial requirements are likely to evolve based on R&D findings, refinement of operational concepts, industry advances, and new industry or regulatory policies or standards related to safety assurance

    Kernel methods with mixed data types and their applications

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    Support Vector Machines (SVMs) represent a category of supervised machine learning algorithms that find extensive application in both classification and regression tasks. In these algorithms, kernel functions are responsible for measuring the similarity between input samples to generate models and perform predictions. In order for SVMs to tackle data analysis tasks involving mixed data, the implementation of a valid kernel function for this purpose is required. However, in the current literature, we hardly find any kernel function specifically designed to measure similarity between mixed data. In addition, there is a complete lack of significant examples where these kernels have been practically implemented. Another notable characteristic of SVMs is their remarkable efficacy in addressing high-dimensional problems. However, they can become inefficient when dealing with large volumes of data. In this project, we propose the formulation of a kernel function capable of accurately capturing the similarity between samples of mixed data. We also present an SVM algorithm based on Bagging techniques that enables efficient analysis of large volumes of data. Additionally, we implement both proposals in an updated version of the successful SVM library LIBSVM. Moreover, we evaluate their effectiveness, robustness and efficiency, obtaining promising results
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