This paper develops a performance index that can be used to find the optimal design parameters of the observer-based residual generator and adaptive threshold of a fault detection scheme for a class of nonlinear systems. The performance of the fault detection scheme is analyzed with respect to the fault detectability of incipient sensor faults, which depends on the dynamic behavior of the residual and the adaptive threshold generator. The proposed performance index is based on the distance between two limit sets that are guaranteed to include the residual under fault-free and faulty conditions. The novelty of this distance metric stems from the parametrization of the limit sets in relation to (i) the design parameters of both the residual generator and adaptive threshold, (ii) the bounds on the system disturbances and measurement noise, and (iii) the fault function and evolution rate. An optimization problem is formulated for finding the design parameters of the fault detection scheme such that the set of guaranteed strongly detectable faults is maximized, where this set is defined based on the distance between the separated fault-free and faulty limit set.@en

The automatic preservation of the indoor air quality (IAQ) is an important task of the intelligent building design in order to ensure the health and safety of the occupants. The IAQ, however, is often compromised by various airborne contaminants that penetrate the indoor environment as a result of accidents or planned attacks. In this paper, we provide the detailed analysis, implementation, and evaluation of a distributed methodology for detecting and isolating multiple contaminant events in large-scale buildings. Specifically, we consider the building as a collection of interconnected subsystems, and we design a contaminant event monitoring software agent for each subsystem. Each monitoring agent aims to detect the contaminant and isolate the zone where the contaminant source is located, while it is allowed to exchange information with its neighboring agents. For configuring the subsystems, we implement both exact and heuristic partitioning solutions. A main contribution of this paper is the investigation of the impact of the partitioning solution on the performance of the distributed contaminant detection and isolation (CDI) scheme with respect to the detectability and isolability of the contaminant sources. The performance of the proposed distributed CDI methodology is demonstrated using the models of real building case studies created on CONTAM.1 1CONTAM is a multizone simulation program developed by the U.S. National Institute of Standards and Technology.@en

Indoor Air Quality monitoring is an essential ingredient of intelligent buildings. The release of various airborne contaminants into the buildings, compromises the health and safety of occupants. Therefore, early contaminant detection is of paramount importance for the timely activation of proper contingency plans in order to minimize the impact of contaminants on occupants health. The objective of this work is to enhance the performance of a distributed contaminant detection methodology, in terms of the minimum detectable contaminant release rates, by considering the joint problem of partitioning selection and observer gain design. Towards this direction, a detectability analysis is performed to derive appropriate conditions for the minimum guaranteed detectable contaminant release rate for specific partitioning configuration and observer gains. The derived detectability conditions are then exploited to formulate and solve an optimization problem for jointly selecting the partitioning configuration and observer gains that yield the best contaminant detection performance.@en

This paper presents an optimization methodology for the design of an observer-based sensor fault detection scheme for a class of nonlinear systems. Taking into account bounded system disturbances and measurement noise, we design an observer aiming at maximizing the set of faults that are guaranteed to be strongly detectable. Strong fault detectability conditions are derived based on the limit sets that bound the residual under healthy and faulty conditions. A novel optimization method is designed based on the separation of the healthy and faulty limit sets. The distance between these sets represents the trade-off between robustness and sensor fault sensitivity. Simulation results are used to show the effectiveness of the proposed methodology applied to a simple example of a flexible link robot.@en