Sebastian Tornil-Sin

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This paper presents a new method for leak localization in Water Distribution Networks that uses a model-based approach combined with Bayesian reasoning. Probability density functions in model-based pressure residuals are calibrated off-line for all the possible leak scenarios by using a hydraulic simulator, being leak size uncertainty, demand uncertainty(More)
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, the problem of robust fault diagnosis of proton exchange membrane (PEM) fuel cells is addressed by introducing the Takagi-Sugeno (TS) interval observers that consider uncertainty in a bounded context, adapting TS observers to the so-called interval approach. Design conditions for the TS interval observer based on regional pole placement are(More)
This paper deals with the problem of set-membership identi cation of nonlinear-in-the-parameters models. To solve this problem, the paper illustrates how the Bayesian approach can be used to determine the feasible parameter set (FPS) by assuming uniform distributed estimation error and at model prior probability distributions. The key point of the(More)
This paper deals with the problem of set-membership identification and fault detection using a Bayesian framework. The paper presents how the setmembership 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 between(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)