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Thomas Lombaerts

Bio: Thomas Lombaerts is an academic researcher from Ames Research Center. The author has contributed to research in topics: Adaptive control & Envelope (motion). The author has an hindex of 22, co-authored 67 publications receiving 1561 citations. Previous affiliations of Thomas Lombaerts include Delft University of Technology & German Aerospace Center.


Papers
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Book
01 Jan 2010
TL;DR: In this paper, the authors present a real-time assessment and evaluation of Fault Tolerant Flight Control (FTC) designs in the SIMONA Research Flight Simulator using online physical model identification.
Abstract: Surviving the Improbable: Towards Resilient Aircraft Control.- Fault Tolerant Flight Control - A Survey.- Fault Detection and Diagnosis for Aeronautic and Aerospace Missions.- Real-Time Identification of Aircraft Physical Models for Fault Tolerant Flight Control.- Industrial Practices in Fault Tolerant Control.- RECOVER: The Benchmark Challenge.- RECOVER: A Benchmark for Integrated Fault Tolerant Flight Control Evaluation.- Assessment Criteria as Specifications for Reconfiguring Flight Control.- Design Methods and Benchmark Analysis.- Fault Tolerant Control Using Sliding Modes with On-Line Control Allocation.- An Adaptive Fault-Tolerant FCS for a Large Transport Aircraft.- Subspace Predictive Control Applied to Fault-Tolerant Control.- Fault-Tolerant Control through a Synthesis of Model-Predictive Control and Nonlinear Inversion.- A FTC Strategy for Safe Recovery against Trimmable Horizontal Stabilizer Failure with Guaranteed Nominal Performance.- Flight Control Reconfiguration Based on Online Physical Model Identification and Nonlinear Dynamic Inversion.- A Combined Fault Detection, Identification and Reconfiguration System Based around Optimal Control Allocation.- Detection and Isolation of Actuator/Surface Faults for a Large Transport Aircraft.- Real-Time Flight Simulator Assessment.- Real-Time Assessment and Piloted Evaluation of Fault Tolerant Flight Control Designs in the SIMONA Research Flight Simulator.- Piloted Evaluation Results of a Nonlinear Dynamic Inversion Based Controller Using Online Physical Model Identification.- Model Reference Sliding Mode FTC with SIMONA Simulator Evaluation: EL AL Flight 1862 Bijlmermeer Incident Scenario.- Conclusions.- Industrial Review.- Concluding Remarks.

198 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present a study on fault tolerant flight control of a benchmark aircraft model, which is implemented by making use of adaptive nonlinear dynamic inversion for manual and autopilot control.
Abstract: This paper presents a study on fault tolerant flight control of a benchmark aircraft model. Reconfiguring control is implemented by making use of adaptive nonlinear dynamic inversion for manual and autopilot control. The weakness of classical nonlinear dynamic inversion, its sensitivity to modeling errors, is circumvented here by making use of a real-time identified physical model of the damaged aircraft. With help of the Boeing 747 benchmark simulation model, including the realistic component as well as the structural failure modes, it is possible to analyze the damage accommodation capabilities of the considered approach. In failure conditions, the damaged aircraft model is identified by the so-called two-step method in real time and this model is applied subsequently to the model-based adaptive nonlinear dynamic inversion routine in a modular structure, which allows flight control reconfigurations online. After discussing the modular adaptive controller setup, reconfiguration test results are shown for damaged aircraft models using a desktop computer as well as the moving base Simulation, Motion, and Navigation Research Flight Simulator of Delft University. These results indicate satisfactory failure handling capabilities of this fault tolerant control setup, for component as well as structural failures.

87 citations

Journal ArticleDOI
TL;DR: In this article, a new recursive algorithm for the approximation of time varying nonlinear aerodynamic models by means of a joint adaptive selection of the model structure and parameter estimation is described. But this algorithm is only suitable for indirect fault tolerant flight control, making use of model based adaptive control routines.
Abstract: This paper describes a new recursive algorithm for the approximation of time varying nonlinear aerodynamic models by means of a joint adaptive selection of the model structure and parameter estimation. This procedure is called Adaptive Recursive Orthogonal Least Squares (AROLS), and is an extension and modification of the classical Recursive Orthogonal Least Squares (ROLS). This algorithm is considered to be particularly useful for indirect fault tolerant flight control, making use of model based adaptive control routines. After the failure, a completely new aerodynamic model can be elaborated recursively with respect to structure as well as parameter values. The performance of the identification algorithm is demonstrated on some simulation data sets.

83 citations

Proceedings ArticleDOI
21 Aug 2006
TL;DR: In this article, the authors present a description of a large transp ort aircraft simulation benchmark that includes a suitable set of assessment criteria for the integrated evaluation of fault tolerant flight control systems (FTFC).
Abstract: This paper presents a description of a large transp ort aircraft simulation benchmark that includes a suitable set of assessment criteria , for the integrated evaluation of fault tolerant flight control systems (FTFC). These syste ms consist of a combination of novel fault detection, isolation (FDI) and reconfigurable contr ol schemes. In 2004, a research group on Fault Tolerant Control, comprising a collaboration of nine European partners from industry, universities and research institutions, w as established within the framework of the Group for Aeronautical Research and Technology in Europe (GARTEUR) co-operation program. The aim of the research group, Flight Mechanics Action Group FM-AG(16), is to demonstrate the capability and viability of modern FTFC schemes when applied to a realistic, nonlinear design problem and to assess t heir capability to improve aircraft survivability. The test scenarios that are an integ ral part of the benchmark were selected to provide challenging assessment criteria to evaluate the effectiveness and potential of the FTFC methods being investigated. The application of fault reconstruction and modelling techniques based on (accident) flight data, as desc ribed in this paper, has resulted in high fidelity non-linear aircraft and fault models for t he design and evaluation of modern FTFC methods.

68 citations


Cited by
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Journal ArticleDOI
01 May 1981
TL;DR: This chapter discusses Detecting Influential Observations and Outliers, a method for assessing Collinearity, and its applications in medicine and science.
Abstract: 1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.

4,948 citations

Journal ArticleDOI
TL;DR: A bibliographical review on reconfigurable fault-tolerant control systems (FTCS) is presented, with emphasis on the reconfiguring/restructurable controller design techniques.

2,455 citations

Journal Article
TL;DR: In this paper, two major figures in adaptive control provide a wealth of material for researchers, practitioners, and students to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs.
Abstract: This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.

1,814 citations

Book ChapterDOI
11 Dec 2012

1,704 citations

Journal ArticleDOI
TL;DR: Chapman and Miller as mentioned in this paper, Subset Selection in Regression (Monographs on Statistics and Applied Probability, no. 40, 1990) and Section 5.8.
Abstract: 8. Subset Selection in Regression (Monographs on Statistics and Applied Probability, no. 40). By A. J. Miller. ISBN 0 412 35380 6. Chapman and Hall, London, 1990. 240 pp. £25.00.

1,154 citations