Search results for: flight-vehicle-system-identification

Flight Vehicle System Identification

Author : R. Jategaonkar
File Size : 67.42 MB
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This valuable volume offers a systematic approach to flight vehicle system identification and exhaustively covers the time domain methodology. It addresses in detail the theoretical and practical aspects of various parameter estimation methods, including those in the stochastic framework and focusing on nonlinear models, cost functions, optimization methods, and residual analysis. A pragmatic and balanced account of pros and cons in each case is provided. The book also presents data gathering and model validation, and covers both large-scale systems and high-fidelity modeling. Real world problems dealing with a variety of flight vehicle applications are addressed and solutions are provided. Examples encompass such problems as estimation of aerodynamics, stability, and control derivatives from flight data, flight path reconstruction, nonlinearities in control surface effectiveness, stall hysteresis, unstable aircraft, and other critical considerations.

Flight Vehicle System Identification

Author : Ravindra V. Jategaonkar
File Size : 39.55 MB
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This book offers a systematic approach to flight vehicle system identification and covers the time-domain methodology. It addresses theoretical and practical aspects of parameter estimation methods, including those in the stochastic framework focusing on nonlinear models, cost function, optimization methods, and residual analysis. A pragmatic and balanced account of pros and cons in each case is provided. It presents data gathering and model validation, covering large-scale and high-fidelity modeling. Real-world problems dealing with a variety of flight vehicle applications are addressed, and solutions are provided. Examples include: estimation of aerodynamic stability and control derivatives from flight data; flight-path reconstruction; nonlinearities in control surface effectiveness; stall hysteresis; unstable aircraft; flexible aircraft model integrating rigid-body and structural dynamics; wake vortex encounters; and other critical considerations. --

Flight Vehicle System Identification

Author : R. Jategaonkar
File Size : 30.14 MB
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This valuable volume offers a systematic approach to flight vehicle system identification and exhaustively covers the time domain methodology. It addresses in detail the theoretical and practical aspects of various parameter estimation methods, including those in the stochastic framework and focusing on nonlinear models, cost functions, optimization methods, and residual analysis. A pragmatic and balanced account of pros and cons in each case is provided. The book also presents data gathering and model validation, and covers both large-scale systems and high-fidelity modeling. Real world problems dealing with a variety of flight vehicle applications are addressed and solutions are provided. Examples encompass such problems as estimation of aerodynamics, stability, and control derivatives from flight data, flight path reconstruction, nonlinearities in control surface effectiveness, stall hysteresis, unstable aircraft, and other critical considerations.

Scientific and Technical Aerospace Reports

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Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.

Flight Test System Identification

Author : Roger Larsson
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With the demand for more advanced fighter aircraft, relying on unstable flight mechanical characteristics to gain flight performance, more focus has been put on model-based system engineering to help with the design work. The flight control system design is one important part that relies on this modeling. Therefore, it has become more important to develop flight mechanical models that are highly accurate in the whole flight envelope. For today’s modern fighter aircraft, the basic flight mechanical characteristics change between linear and nonlinear as well as stable and unstable as an effect of the desired capability of advanced maneuvering at subsonic, transonic and supersonic speeds. This thesis combines the subject of system identification, which is the art of building mathematical models of dynamical systems based on measurements, with aeronautical engineering in order to find methods for identifying flight mechanical characteristics. Here, some challenging aeronautical identification problems, estimating model parameters from flight-testing, are treated. Two aspects are considered. The first is online identification during flight-testing with the intent to aid the engineers in the analysis process when looking at the flight mechanical characteristics. This will also ensure that enough information is available in the resulting test data for post-flight analysis. Here, a frequency domain method is used. An existing method has been developed further by including an Instrumental Variable approach to take care of noisy data including atmospheric turbulence and by a sensor-fusion step to handle varying excitation during an experiment. The method treats linear systems that can be both stable and unstable working under feedback control. An experiment has been performed on a radio-controlled demonstrator aircraft. For this, multisine input signals have been designed and the results show that it is possible to perform more time-efficient flight-testing compared with standard input signals. The other aspect is post-flight identification of nonlinear characteristics. Here the properties of a parameterized observer approach, using a prediction-error method, are investigated. This approach is compared with four other methods for some test cases. It is shown that this parameterized observer approach is the most robust one with respect to noise disturbances and initial offsets. Another attractive property is that no user parameters have to be tuned by the engineers in order to get the best performance. All methods in this thesis have been validated on simulated data where the system is known, and have also been tested on real flight test data. Both of the investigated approaches show promising results.

Flight Test Identification and Simulation of a UH 60A Helicopter and Slung Load

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Helicopter slung-load operations are common in both military and civil contexts. Helicopters and loads are often qualified for these operations by means of flight tests, which can be expensive and time consuming. There is significant potential to reduce such costs both through revisions in flight-test methods and by using validated simulation models. To these ends, flight tests were conducted at Moffett Field to demonstrate the identification of key dynamic parameters during flight tests (aircraft stability margins and handling-qualities parameters, and load pendulum stability), and to accumulate a data base for simulation development and validation. The test aircraft was a UH-60A Black Hawk, and the primary test load was an instrumented 8- by 6- by 6-ft cargo container. Tests were focused on the lateral and longitudinal axes, which are the axes most affected by the load pendulum modes in the frequency range of interest for handling qualities; tests were conducted at airspeeds from hover to 80 knots. Using telemetered data, the dynamic parameters were evaluated in near real time after each test airspeed and before clearing the aircraft to the next test point. These computations were completed in under 1 min. A simulation model was implemented by integrating an advanced model of the UH-60A aerodynamics, dynamic equations for the two-body slung-load system, and load static aerodynamics obtained from wind-tunnel measurements. Comparisons with flight data for the helicopter alone and with a slung load showed good overall agreement for all parameters and test points; however, unmodeled secondary dynamic losses around 2 Hz were found in the helicopter model and they resulted in conservative stability margin estimates.

Flight Dynamics and System Identification for Modern Feedback Control

Author : Jared A Grauer
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Unmanned air vehicles are becoming increasingly popular alternatives for private applications which include, but are not limited to, fire fighting, search and rescue, atmospheric data collection, and crop surveys, to name a few. Among these vehicles are avian-inspired, flapping-wing designs, which are safe to operate near humans and are required to carry payloads while achieving manoeuverability and agility in low speed flight. Conventional methods and tools fall short of achieving the desired performance metrics and requirements of such craft. Flight dynamics and system identification for modern feedback control provides an in-depth study of the difficulties associated with achieving controlled performance in flapping-wing, avian-inspired flight, and a new model paradigm is derived using analytical and experimental methods, with which a controls designer may then apply familiar tools. This title consists of eight chapters and covers flapping-wing aircraft and flight dynamics, before looking at nonlinear, multibody modelling as well as flight testing and instrumentation. Later chapters examine system identification from flight test data, feedback control and linearization. Presents experimental flight data for validation and verification of modelled dynamics, thus illustrating the deficiencies and difficulties associated with modelling flapping-wing flight Derives a new flight dynamics model needed to model avian-inspired vehicles, based on nonlinear multibody dynamics Extracts aerodynamic models of flapping flight from experimental flight data and system identification techniques

Identification Modeling and Characteristics of Miniature Rotorcraft

Author : Bernard Mettler
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Identification Modeling and Characteristics of Miniature Rotorcraft introduces an approach to developing a simple and effective linear parameterized model of vehicle dynamics using the CIFERâ identification tool created by the Army/NASA Rotorcraft Division. It also presents the first application of the advanced control system optimization tool CONDUITâ to systematically and efficiently tune control laws for a model-scale UAV helicopter against multiple and competing dynamic response criteria. Identification Modeling and Characteristics of Miniature Rotorcraft presents the detailed account of how the theory was developed, the experimentation performed, and how the results were used. This book will serve as a basic and illustrative guide for all students that are interested in developing autonomous flying helicopters.

Rotorcraft System Identification

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Identification Des Syst mes Pour Le D veloppement Int gr Des A ronefs Et Les Essais en Vol

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Government Reports Announcements Index

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Flight vehicle Materials Structures and Dynamics assessment and Future Directions Structural dynamics and aeroelasticity

Author : Ahmed Khairy Noor
File Size : 40.27 MB
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The fifth volume of a six-volume monograph, the objective of which is to broaden the awareness among material scientists, engineers, and research workers about the recent developments which can impact future flight vehicles. The present volume, Volume 5, is divided into three parts. The first part h

AIAA Journal

Author : American Institute of Aeronautics and Astronautics
File Size : 47.56 MB
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International Aerospace Abstracts

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Indian Science Abstracts

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File Size : 75.22 MB
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Government Reports Annual Index

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File Size : 66.17 MB
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Aerospace America

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File Size : 51.69 MB
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NASA SP

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File Size : 74.94 MB
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Flight vehicle Materials Structures and Dynamics Computational structures technology

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File Size : 74.74 MB
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Aeronautical Engineering

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File Size : 70.29 MB
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A selection of annotated references to unclassified reports and journal articles that were introduced into the NASA scientific and technical information system and announced in Scientific and technical aerospace reports (STAR) and International aerospace abstracts (IAA)