Non-linear aircraft flight path reconstruction review and new advances

Mulder, J.A.; Chu, Q.P.; Sridhar, J.K.; Breeman, J.H.; Laban, M.

doi:10.1016/s0376-0421(99)00005-6

Cited by 100 publications

(61 citation statements)

References 30 publications

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“…[34][35][36][37] There are many other identification algorithms mentioned in the literature such as maximum likelihood identification (MLI) and other one step identification routines, but not all of them are applicable to real time embedded computation. One of the few procedures which can be implemented in real time is the filtering method developed at the German Aerospace Research Center DLR.…”

Section: A Identification: Two Step Methodsmentioning

confidence: 99%

Piloted Simulator Evaluation Results of New Fault-Tolerant Flight Control Algorithm

Lombaerts

Smaïli

Stroosma

et al. 2010

AIAA Guidance, Navigation, and Control Conference

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A high fidelity aircraft simulation model, reconstructed using the Digital Flight Data Recorder (DFDR) of the 1992 Amsterdam Bijlmermeer aircraft accident (Flight 1862), has been used to evaluate a new Fault-Tolerant Flight Control Algorithm in an online piloted evaluation. This paper focuses on the piloted simulator evaluation results. Reconfiguring control is implemented by making use of Adaptive Nonlinear Dynamic Inversion (ANDI) for manual fly by wire control. After discussing the modular adaptive controller setup, the experiment is described for a piloted simulator evaluation of this innovative reconfigurable control algorithm applied to a damaged civil transport aircraft. The evaluation scenario, measurements and experimental design, as well as the real-time implementation are described. Finally, reconfiguration test results are shown for damaged aircraft models including component as well as structural failures. The evaluation shows that the FTFC algorithm is able to restore conventional control strategies after the aircraft configuration has changed dramatically due to these severe failures. The algorithm supports the pilot after a failure by lowering workload and allowing a safe return to the airport. For most failures, the handling qualities are shown to degrade less with a failure than the baseline classical control system does.

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Section: A Identification: Two Step Methodsmentioning

confidence: 99%

Piloted Simulator Evaluation Results of New Fault-Tolerant Flight Control Algorithm

Lombaerts

Smaïli

Stroosma

et al. 2010

AIAA Guidance, Navigation, and Control Conference

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“…al. 38 based on an iterated extended Kalman filter was used to obtain crisp aircraft states. In Fig.…”

Section: Results From the Flight Testingmentioning

confidence: 99%

“…38 The linear regression scheme for multivariate simplex splines from Sec. III was then used with the reconstructed aircraft state to identify spline based models for the non-dimensional aerodynamic force coefficients C X , C Z and the non-dimensional aerodynamic moment coefficients C l , C m and C n .…”

Section: Aerodynamic Model Identification Of the Cessna Citation IImentioning

confidence: 99%

A Multidimensional Spline-Based Global Nonlinear Aerodynamic Model for the Cessna Citation II

Visser

Mulder

Chu

2010

AIAA Atmospheric Flight Mechanics Conference

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A new method is proposed for the identification of global nonlinear models of aircraft non-dimensional force and moment coefficients. The method is based on a recent type of multivariate spline, the multivariate simplex spline, which can accurately approximate very large, scattered nonlinear datasets in any number of dimensions. The new identification method is used to identify a global nonlinear aerodynamic model of high dimensionality for the Cessna Citation II laboratory aircraft operated by the Delft University of Technology and the Netherlands National Aerospace Laboratory. The data used in the identification process consisted of millions of measurements and was accumulated during more than 250 flight test maneuvers with the laboratory aircraft. The resulting models for the aerodynamic force and moment coefficients are continuous analytical functions as they consist of sets of piecewise defined, multivariate polynomials. The identified models were validated using a subset of the flight data, with validation results showing a very close match between model and reality.

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“…21 Flight path reconstruction techniques based on an iterated extended Kalman filter (IEKF) were used to get a crisp estimation of aircraft state. 32 The linear regression scheme for multivariate simplex splines from Sec. II was then used with the reconstructed aircraft state to identify a simplex spline based model for the non-dimensional aerodynamic pitching moment coefficient C m .…”

Section: Aerodynamic Model Validationmentioning

confidence: 99%

Validating the Multidimensional Spline Based Global Aerodynamic Model for the Cessna Citation II

Visser

Mulder

2011

AIAA Atmospheric Flight Mechanics Conference

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The validation of aerodynamic models created using flight test data is a time consuming and often costly process. In this paper a new method for the validation of global nonlinear aerodynamic models based on multivariate simplex splines is presented. This new method uses the unique properties of the multivariate simplex splines, a recent type of of multivariate spline, to speedup the process of aerodynamic model validation. Multivariate simplex splines are defined on non-rectangular domains and can be used to accurately fit scattered nonlinear datasets in any number of dimensions. The simplex splines consist of piecewise defined, ordinary multivariate polynomials with a predefined continuity between neighboring polynomial pieces. A recent method for nonlinear system identification based on multivariate simplex splines was used to create a global nonlinear aerodynamic model of the Cessna Citation II laboratory aircraft operated by the Delft University of Technology. In this paper, the multivariate spline based aerodynamic model for the pitching moment coefficient will be validated using both a model residual analysis as well as a statistical model quality analysis. It will be demonstrated that these new analysis methods, which are both unique to the multivariate simplex splines, provide a highly efficient and powerful new method for aerodynamic model validation.

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Non-linear aircraft flight path reconstruction review and new advances

Cited by 100 publications

References 30 publications

Piloted Simulator Evaluation Results of New Fault-Tolerant Flight Control Algorithm

Piloted Simulator Evaluation Results of New Fault-Tolerant Flight Control Algorithm

A Multidimensional Spline-Based Global Nonlinear Aerodynamic Model for the Cessna Citation II

Validating the Multidimensional Spline Based Global Aerodynamic Model for the Cessna Citation II

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