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Time filter

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Lisbon, Portugal

Bras S.,University of Lisbon | Rosa P.,DEIMOS Engineering | Silvestre C.,University of Lisbon | Silvestre C.,Macau University of Science and Technology | Oliveira P.,University of Lisbon
Systems and Control Letters | Year: 2013

The problem of attitude and rate gyro bias estimation is addressed by resorting to measurements acquired from rate gyros and vector observations. A Set-Valued Observer (SVO) is proposed that has no singularities and that, for any initial conditions, provides a bounding set with guarantees of containing the actual (unknown) rotation matrix. The sensor readings are assumed to be corrupted by bounded measurement noise and constant gyro bias. Conditions for the boundedness of the estimated sets are established and implementation details are discussed. The feasibility of the technique is demonstrated in simulation. © 2013 Elsevier B.V. All rights reserved. Source


Casau P.,University of Lisbon | Rosa P.,DEIMOS Engineering | Silvestre C.,University of Macau
IFAC Proceedings Volumes (IFAC-PapersOnline) | Year: 2015

In this paper, we present the theoretical background for the implementation of FITBOX - a new, freely available fault isolation toolbox for MATLAB that makes use of novel set-membership methods for Fault Detection and Isolation (FDI). We apply the proposed methods to the FDI of a wind turbine and evaluate their performance in a simulation setting. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. Source


Casau P.,University of Lisbon | Rosa P.,DEIMOS Engineering | Tabatabaeipour S.M.,Technical University of Denmark | Silvestre C.,University of Lisbon | And 2 more authors.
IEEE Transactions on Control Systems Technology | Year: 2014

A complete methodology to design robust fault detection and isolation (FDI) filters and fault-tolerant control (FTC) schemes for linear parameter varying systems is proposed, with particular focus on its applicability to wind turbines. This paper takes advantage of the recent advances in model falsification using set-valued observers (SVOs) that led to the development of FDI methods for uncertain linear time-varying systems, with promising results in terms of the time required to diagnose faults. An integration of such SVO-based FDI methods with robust control synthesis is described, to deploy new FTC algorithms that are able to stabilize the plant under faulty environments. The FDI and FTC algorithms are assessed by resorting to a publicly available wind turbine benchmark model, using Monte Carlo simulation runs. © 2014 IEEE. Source


Bras S.,University of Lisbon | Rosa P.,DEIMOS Engineering | Silvestre C.,University of Lisbon | Silvestre C.,Macau University of Science and Technology | Oliveira P.,University of Lisbon
IEEE Transactions on Automatic Control | Year: 2015

This work addresses the problem of Fault Detection and Isolation (FDI) for navigation systems equipped with sensors providing inertial measurements and vector observations. Assuming upper bounded sensor noise, two strategies are proposed: i) the first one takes advantage of existing hardware redundancy, requiring at least five sensor measurements to isolate faults; ii) the second approach exploits the analytical redundancy between the angular velocity measurements and the vector observations, by resorting to set-valued observers (SVOs). Necessary and sufficient conditions on the magnitude of the faults are provided, in order to guarantee successful detection and isolation, when hardware redundancy is available. Due to the set-based construction of the methods, none of the solutions generates false detections and no decision threshold is required. Using a simulation scenario, the proposed strategies are compared with two alternatives available in the literature. © 2015 IEEE. Source


Rosa P.,DEIMOS Engineering | Silvestre C.,University of Lisbon | Silvestre C.,Macau University of Science and Technology | Athans M.,MIT
International Journal of Robust and Nonlinear Control | Year: 2014

This article introduces a new method for model falsification using set-valued observers, which can be applied to a class of discrete linear time-invariant dynamic systems with time-varying model uncertainties. In comparison with previous results, the main advantages of this approach are as follows: The computation of the convex hull of the set-valued estimates of the state can be avoided under certain circumstances; to guarantee convergence of the set-valued estimates of the state, the required number of previous steps is at most as large as the number of states of the nominal plant; and it provides a straightforward nonconservative method to falsify uncertain models of dynamic systems, including open-loop unstable plants. The results obtained are illustrated in simulation, emphasizing the advantages and shortcomings of the suggested method. Copyright © 2013 John Wiley & Sons, Ltd. Source

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