This paper proposes a distributed methodology for detecting and isolating multiple sensor faults in interconnected cyberphysical systems. The distributed sensor fault detection and isolation process is conducted in the cybersuperstratum, in two levels. The first-level diagnosis is based on the design of monitoring agents, where every agent is dedicated to a corresponding interconnected subsystem. The monitoring agent is designed to isolate multiple sensor faults occurring in the sensor set of the physical part, while it is allowed to exchange information with its neighboring monitoring agents. The second-level diagnosis is realized by applying a global decision logic designed to isolate multiple sensor faults that may propagate in the cybersuperstratum through the exchange of information between monitoring agents. The decision-making process, executed in both levels of diagnosis, relies on a multiple sensor fault combinatorial logic and diagnostic reasoning. The performance of the proposed methodology is analyzed with respect to the sensor fault propagation effects and the distributed sensor fault detectability.@en

The objective of this chapter is to present a methodology for computing robust positively invariant sets for linear, discrete time-invariant systems that are affected by additive disturbances, with the particularity that these disturbances are subject to state-dependent bounds. The proposed methodology requires less restrictive assumptions compared to similar established techniques, while it provides the framework for determining the state-dependent (parameterized) ultimate bounds for several classes of disturbances. The added value of the proposed approach is illustrated by an optimization-based problem for detecting the mode of functioning of a switching system.@en

This paper presents a model-based distributed fault-tolerant control (FTC) scheme with emphasis on compensating the effects of sensor faults in multi-zone heating, ventilating and air-conditioning (HVAC) systems. A bank of local adaptive FTC agents are designed to accommodate possible sensor faults in HVAC systems, modeled as a set of interconnected, nonlinear subsystems. In order to compensate the fault effects that may propagate in the neighboring subsystems, each local FTC utilizes the information generated by a local monitoring agent that diagnoses the sensor faults and performs an adaptive estimation of the isolated sensor faults. The local monitoring and control agents are allowed to exchange information with neighboring agents. Simulation results are used to illustrate the effectiveness of the proposed methodology applied to a seven-zone HVAC system.@en