22 research outputs found

    Framework for state and unknown input estimation of linear time-varying systems

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    The design of unknown-input decoupled observers and filters requires the assumption of an existence condition in the literature. This paper addresses an unknown input filtering problem where the existence condition is not satisfied. Instead of designing a traditional unknown input decoupled filter, a Double-Model Adaptive Estimation approach is extended to solve the unknown input filtering problem. It is proved that the state and the unknown inputs can be estimated and decoupled using the extended Double-Model Adaptive Estimation approach without satisfying the existence condition. Numerical examples are presented in which the performance of the proposed approach is compared to methods from literature.Comment: This paper has been accepted by Automatica. It considers unknown input estimation or fault and disturbances estimation. Existing approaches considers the case where the effects of fault and disturbance can be decoupled. In our paper, we consider the case where the effects of fault and disturbance are coupled. This approach can be easily extended to nonlinear system

    Distance-Fields-Over-Grids Method for Aircraft Envelope Determination

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    Adaptive Incremental Nonlinear Dynamic Inversion for Attitude Control of Micro Air Vehicles

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    Pharmacogenetic meta-analysis of genome-wide association studies of LDL cholesterol response to statins

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    Statins effectively lower LDL cholesterol levels in large studies and the observed interindividual response variability may be partially explained by genetic variation. Here we perform a pharmacogenetic meta-analysis of genome-wide association studies (GWAS) in studies addressing the LDL cholesterol response to statins, including up to 18,596 statin-treated subjects. We validate the most promising signals in a further 22,318 statin recipients and identify two loci, SORT1/CELSR2/PSRC1 and SLCO1B1, not previously identified in GWAS. Moreover, we confirm the previously described associations with APOE and LPA. Our findings advance the understanding of the pharmacogenetic architecture of statin response

    Incremental Nonlinear Fault-Tolerant Control of a Quadrotor With Complete Loss of Two Opposing Rotors

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    In order to further expand the flight envelope of quadrotors under actuator failures, we design a nonlinear sensor-based fault-tolerant controller to stabilize a quadrotor with failure of two opposing rotors in the high-speed flight condition (>8 m/s). The incremental nonlinear dynamic inversion approach which excels in handling model uncertainties is adopted to compensate for the significant unknown aerodynamic effects. The internal dynamics of such an underactuated system have been analyzed, and subsequently stabilized by redefining the control output. The proposed method can be generalized to control a quadrotor under single-rotor-failure and nominal conditions. For validation, flight tests have been carried out in a large-scale open jet wind tunnel. The position of a damaged quadrotor can be controlled in the presence of significant wind disturbances. A linear quadratic regulator approach from the literature has been compared to demonstrate the advantages of the proposed nonlinear method in the windy and high-speed flight condition

    Design and simulation of fault tolerant flight control based on a physical approach

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    This paper presents a study on fault tolerant flight control of a benchmark aircraft model, using a physical modular approach. Reconfiguring control is implemented by making use of adaptive nonlinear dynamic inversion for 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 in real time by the two-step method and this model is applied subsequently to the model-based adaptive nonlinear dynamic inversion routine in a modular structure, which allows flight control reconfiguration on-line. Pseudo Control Hedging is included to guarantee that no unachievable reference commands are given to the system, which would otherwise result in control effector saturation. Various simulated reconfiguration test results are shown for damaged aircraft models. These results indicate satisfactory failure handling capabilities of this fault tolerant control setup, for component as well as structural failures

    Quadrotor Gray-Box Model Identification from High-Speed Flight Data

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    2nd CEAS Specialist Conference on Guidance, Navigation and Control

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    Following the successful 1st CEAS (Council of European Aerospace Societies) Specialist Conference on Guidance, Navigation and Control (CEAS EuroGNC) held in Munich, Germany in 2011, Delft University of Technology happily accepted the invitation of organizing the 2nd  CEAS EuroGNC in Delft, The Netherlands in 2013. The goal of the conference is to promote new advances in aerospace GNC theory and technologies for enhancing safety, survivability, efficiency, performance, autonomy and intelligence of aerospace systems using on-board sensing, computing and systems. A great push for new developments in GNC are the ever higher safety and sustainability requirements in aviation. Impressive progress was made in new research fields such as sensor and actuator fault detection and diagnosis, reconfigurable and fault tolerant flight control, online safe flight envelop prediction and protection, online global aerodynamic model identification, online global optimization and flight upset recovery. All of these challenges depend on new online solutions from on-board computing systems. Scientists and engineers in GNC have been developing model based, sensor based as well as knowledge based approaches aiming for highly robust, adaptive, nonlinear, intelligent and autonomous GNC systems. Although the papers presented at the conference and selected in this book could not possibly cover all of the present challenges in the GNC field, many of them have indeed been addressed and a wealth of new ideas, solutions and results were proposed and presented. For the 2nd CEAS Specialist Conference on Guidance, Navigation and Control the International Program Committee conducted a formal review process. Each paper was reviewed in compliance with good journal practice by at least two independent and anonymous reviewers. The papers published in this book were selected from the conference proceedings based on the results and recommendations from the reviewers.    
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