Albert Rosich

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The problem of optimal sensor placement for FDI consists in determining the set of sensors that minimizes a pre-defined cost function satisfying at the same time a preestablished set of FDI specifications for a given set of faults. The main contribution of this paper is to propose an algorithm for model-based FDI sensor placement based on formulating a(More)
This paper presents the application of a new methodology for Fault Detection and Isolation (FDI) to a Fuel Cell System. The work is devoted to find an optimal set of sensors for model-based FDI. The novelty is that binary integer linear programming (BILP) is used in the optimization formulation, leading to a reformulation of the detectability and(More)
This work focuses on residual generation for modelbased fault diagnosis. Specifically, a methodology to derive residual generators when non-linear equations are present in the model is developed. A main result is the characterization of computational sequences that are particularly easy to implement as residual generators and that take causal information(More)
This paper proposes a new sensor placement approach for leak location in water distribution networks (WDNs). The sensor placement problem is formulated as an integer optimization problem. The optimization criterion consists in minimizing the number of non-isolable leaks according to the isolability criteria introduced. Because of the large size and(More)
The problem of optimal sensor placement for FDI consists in determining the set of sensors that minimizes a pre-defined cost function satisfying at the same time a pre-established set of FDI specifications for a given set of faults. Existing approaches are mainly based on formulating an optimization problem once the sets of all possible ARRs has been(More)
Abstract: This work is devoted to find an optimal set of sensors for model-based FDI. The novelty is that binary integer linear programming is used in the optimization problem, leading to a formulation of the detectability and isolability specifications as linear inequality constraints. Furthermore, a very detailed system model is not needed since the(More)
The paper presents a new approach for control security. Specifically, cyber-attacks on the controller are investigated by means of optimization techniques in order to determine the worst-case scenario. Then, a novel attack detector based on limit checking is introduced. The particularity of this detector is that no specific controller knowledge is(More)
Based on frequency-domain transformation technique, this paper proposes an attack detection scheme for stochastic control systems under stochastic cyber-attacks and disturbances. The focus is on designing an anomaly detector for the stochastic control systems. First, we construct a model of stochastic control system with stochastic cyber-attacks which(More)
This work aims to study which sensors are required to be installed in a process in order to improve certain fault diagnosis specifications. Especially, the present method is based on structural models. Thus, system models involving a wide variety of equations (e.g. linear, non-linear algebraic, dynamics) can be easy handled. The use of structural models(More)
This work develops a methodology to solve the sensor placement problem for fault detection and isolation. The proposed methodology is suitable to handle highly non-linear and large scale systems since it is based on structural models. Furthermore, causality is assigned in those variable-equation relations that the variable can be computed from the equation(More)