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  • 1
    Unknown
    New York : Academic Press
    Keywords: DDC 519.7/03 ; LC T57.83 ; Dynamic programming ; Stochastic control theory
    Pages: Online-Ressource (xi, 593 pages)
    ISBN: 9780124879508
    Language: English
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  • 2
    Publication Date: 2013-08-31
    Description: Information is given in the form of outlines, graphs, tables and charts. Topics include system identification, Bayesian statistical decision theory, Maximum Likelihood Estimation, identification methods, structural mode identification using a stochastic realization algorithm, and identification results regarding membrane simulations and X-29 flutter flight test data.
    Keywords: SPACECRAFT DESIGN, TESTING AND PERFORMANCE
    Type: NASA. Langley Research Center, Fourth NASA Workshop on Computational Control of Flexible Aerospace Systems, Part 2; p 845-880
    Format: application/pdf
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  • 3
    Publication Date: 2019-07-13
    Description: This paper describes model structures and parameter estimation algorithms suitable for the identification of unsteady aerodynamic models from input-output data. The model structures presented are state space models and include linear time-invariant (LTI) models and linear parameter-varying (LPV) models. They cover a wide range of local and parameter dependent identification problems arising in unsteady aerodynamics and nonlinear flight dynamics. We present a residue algorithm for estimating model parameters from data. The algorithm can incorporate apriori information and is described in detail. The algorithms are evaluated on the F-16XL wind-tunnel test data from NAS Langley Research Center. Results of numerical evaluation are presented. The paper concludes with a discussion major issues and directions for future work.
    Keywords: Aerodynamics
    Type: AIAA Guidance, Navigation, and Control Conference and Exhibit; Aug 15, 2005 - Aug 18, 2005; San Francisco, CA; United States
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  • 4
    Publication Date: 2019-07-13
    Description: As more and more nonlinear estimation techniques become available, our interest is in finding out what performance improvement, if any, they can provide for practical nonlinear problems that have been traditionally solved using linear methods. In this paper we examine the problem of estimating spacecraft position using conical scan (conscan) for NASA's Deep Space Network antennas. We show that for additive disturbances on antenna power measurement, the problem can be transformed into a linear one, and we present a general solution to this problem, with the least square solution reported in literature as a special case. We also show that for additive disturbances on antenna position, the problem is a truly nonlinear one, and we present two approximate solutions based on linearization and Unscented Transformation respectively, and one 'exact' solution based on Markov Chain Monte Carlo (MCMC) method. Simulations show that, with the amount of data collected in practice, linear methods perform almost the same as MCMC methods. It is only when we artificially reduce the amount of collected data and increase the level of noise that nonlinear methods show significantly better accuracy than that achieved by linear methods, at the expense of more computation.
    Keywords: Theoretical Mathematics
    Type: Conference on Signal Processing, Sensor Funsion, and Target Recognition XIV; Mar 28, 2005; Orlando, FL; United States
    Format: text
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  • 5
    Publication Date: 2019-07-13
    Description: In this paper we present an integrated approach to in-flight damage accommodation in flight control. The approach is based on Multiple Models, Switching and Tuning (MMST), and consists of three steps: In the first step the main objective is to acquire a realistic aircraft damage model. Modeling of in-flight damage is a highly complex problem since there is a large number of issues that need to be addressed. One of the most important one is that there is strong coupling between structural dynamics, aerodynamics, and flight control. These effects cannot be studied separately due to this coupling. Once a realistic damage model is available, in the second step a large number of models corresponding to different damage cases are generated. One possibility is to generate many linear models and interpolate between them to cover a large portion of the flight envelope. Once these models have been generated, we will implement a recently developed-Model Set Reduction (MSR) technique. The technique is based on parameterizing damage in terms of uncertain parameters, and uses concepts from robust control theory to arrive at a small number of "centered" models such that the controllers corresponding to these models assure desired stability and robustness properties over a subset in the parametric space. By devising a suitable model placement strategy, the entire parametric set is covered with a relatively small number of models and controllers. The third step consists of designing a Multiple Models, Switching and Tuning (MMST) strategy for estimating the current operating regime (damage case) of the aircraft, and switching to the corresponding controller to achieve effective damage accommodation and the desired performance. In the paper present a comprehensive approach to damage accommodation using Model Set Design,MMST, and Variable Structure compensation for coupling nonlinearities. The approach was evaluated on a model of F/A-18 aircraft dynamics under control effector damage, augmented by nonlinear cross-coupling terms and a structural dynamics model. The proposed approach achieved excellent performance under severe damage effects.
    Keywords: Aircraft Stability and Control
    Type: AIAA Paper 2008-6504 , LF99-7796 , AIAA Guidance, Navigation and Control Conference and Exhibit; Aug 18, 2008 - Aug 21, 2008; Honolulu, HI; United States
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