Sebastian Tornil-Sin

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In this paper, the robust fault detection problem for non-linear systems considering both bounded parametric modelling errors and measurement noises is addressed. The non-linear system is monitored by using a state estimator with bounded modelling uncertainty and bounded process and measurement noises. Additionally, time-variant and time-invariant system(More)
—In this paper, the robust fault diagnosis problem for non-linear systems considering both bounded parametric modelling errors and noises is addressed using parity equation based Analytical Redundancy Relations and Interval Constraint Satisfaction techniques. Fault detection, isolation and estimation tasks are considered. Moreover, the paper addresses the(More)
In this paper, an approach to design an Admissible Model Matching (AMM) Fault Tolerant Control (FTC) based on Linear Parameter Varying (LPV) fault representation is proposed. The main contribution of this approach is to consider the fault as a scheduling variable that allows the controller reconfiguration online. The fault is expressed as a change in the(More)
In this paper, a new approach to design a Fault-Tolerant Control (FTC) based on Linear Parameter Varying (LPV) Admissible Model Matching (AMM) is proposed. The suggested strategy is an active technique that requires the fault to be detected and estimated by the FDI scheme. Then, the controller is redesigned accordingly. In this work, faults are expressed as(More)
— This paper deals with the problem of set-membership identification and fault detection using a Bayesian framework. The paper presents how the set-membership model estimation problem can be reformulated from a Bayesian viewpoint in order to, firstly, determine the feasible parameter set in the identification stage and, secondly, check the consistency(More)
This paper deals with the problem of nonlinear set-membership identification. To solve this problem, a Bayesian approach is introduced and compared with the subpavings approach. The paper illustrates how the Bayesian approach can be used to determine the feasible parameter set and to check the consistency between measurement data and model. In particular,(More)
In this paper, the robust fault diagnosis problem for non-linear systems considering both bounded parametric modelling errors and noises is addressed using constraints satisfaction. Combining available measurements with the model of the monitored system, a set of analytical redundancy relations (ARR), relating only known variables, can be derived. These(More)