{"id":95661,"date":"2018-03-11T10:15:41","date_gmt":"2018-03-11T10:15:41","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/sin-categoria\/robust-fault-detection-and-tolerance-evaluation-using-zonotopes\/"},"modified":"2018-03-11T10:15:41","modified_gmt":"2018-03-11T10:15:41","slug":"robust-fault-detection-and-tolerance-evaluation-using-zonotopes","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/tecnologia-de-la-automatizacion\/robust-fault-detection-and-tolerance-evaluation-using-zonotopes\/","title":{"rendered":"Robust fault detection and tolerance evaluation using zonotopes"},"content":{"rendered":"<h2>Tesis doctoral de <strong> Pedro Luis Guerra Brito <\/strong><\/h2>\n<p>Model-based fault detection is based on the use of mathematical models of the  monitored system. Reliability and performance of fault detection algorithms depend on  the quality of the model used. These algorithms can often be improved by refining the  models they are based on. However, high  fidelity models are costly and modelling  errors and disturbances in complex engineering systems are inevitable. Hence there is a  need to develop robust fault detection algorithms where model uncertainty is explicitly  taken into account. The robustness of a fault  detection system indicates its ability to  distinguish between faults on the one hand and model uncertainty and disturbances on  the other hand.    the robust fault detection research has roughly focused on two distinct approaches. In  one of the approaches, characterized as active, the central idea is to decouple the effect  of the uncertainty. The other approach, known as passive, is based on enhancing the  robustness of the fault detection system at the decision-making stage. The aim with the  passive approach is usually to determine, given a set of models, if there is any member  in the set that can explain the measurements.    when a measurement is found to be inconsistent with this set, a fault is assumed to have  occurred. As an exact representation of the set of parameters or states consistent with  the measurements is hard to calculate,  outer bounds are often  used instead, using  algorithms coming from set-membership estimation. This is the approach adopted in  this thesis.     set-membership estimation methods have been the subject of a number of publications.  they can be classified according to how the approximation of the feasible solution set is  represented or parameterized. In other study the set was over bounded by an ellipsoid.  other authors have focused on orthotopic approximations. Set-membership algorithms  have been already applied to fault detection.     in the current thesis, the robust fault detection is studied using zonotopes, which include  as a special case parallelotopes. This thesis will show that the zonotope representation  of the uncertainty combined with the above mentioned identification methods, is  particularly suitable for fault detection.    as an extension of the use of set representation with zonotopes, this thesis presents a  computational procedure to evaluate fault-tolerance of linear constrained model  predictive control (lcmpc) in case of a given actuator fault configuration (afc).  faults in actuators cause changes in the constraints on the control signals which in turn  change the set of feasible solutions. This may derive in an empty set of admissible  solutions for the control objective. Therefore, the admissibility of the control law facing  the actuator faults can be determined knowing the feasible  solutions set. This thesis  presents a method to compute this set and then evaluate the admissibility of the control  law. In particular, the admissible solutions set for the predictive control problem  including the effect of faults is determined using an algorithm that uses set  computations based on zonotopes.<\/p>\n<p>&nbsp;<\/p>\n<h3>Datos acad\u00e9micos de la tesis doctoral \u00ab<strong>Robust fault detection and tolerance evaluation using zonotopes<\/strong>\u00ab<\/h3>\n<ul>\n<li><strong>T\u00edtulo de la tesis:<\/strong>\u00a0 Robust fault detection and tolerance evaluation using zonotopes <\/li>\n<li><strong>Autor:<\/strong>\u00a0 Pedro Luis Guerra Brito <\/li>\n<li><strong>Universidad:<\/strong>\u00a0 Polit\u00e9cnica de catalunya<\/li>\n<li><strong>Fecha de lectura de la tesis:<\/strong>\u00a0 27\/07\/2009<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h3>Direcci\u00f3n y tribunal<\/h3>\n<ul>\n<li><strong>Director de la tesis<\/strong>\n<ul>\n<li>Vicenc Puig Cayuela<\/li>\n<\/ul>\n<\/li>\n<li><strong>Tribunal<\/strong>\n<ul>\n<li>Presidente del tribunal: fatiha Nejjari <\/li>\n<li>Jos\u00e9 Manuel Bravo caro (vocal)<\/li>\n<li>  (vocal)<\/li>\n<li>  (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tesis doctoral de Pedro Luis Guerra Brito Model-based fault detection is based on the use of mathematical models of the 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