The aim of this paper is to propose a model-based feedback control strategy for indoor temperature regulation in buildings equipped with underfloor air distribution (UFAD). Supposing distributed sensing and actuation capabilities, a 0−D model of the ventilation process is first derived, based on the thermodynamics properties of the flow. A state-space description of the process is then inferred, including discrete events modeled by Markovian processes. This results in a hybrid model with nonlinear components. The use of a wireless sensor network (WSN) and the resulting communication constraints are also discussed. A H ∞ MIMO controller is finally proposed and shown to effectively handle the discrete and nonlinear perturbations.
Industrial control systems rely more and more on digital technologies. Although the cyber risk such technologies induce is widely judged as serious, especially for critical infrastructures, these systems have generally not been designed to serve cybersecurity purposes. Instead they were thought first for serving operational efficiency. It thus becomes critical to study cyber threats in industrial environments and experimental test beds are needed to evaluate risks, physical consequences of cyber incidents, and performance of countermeasures. The test bed we present here focuses on studying cyber risks and their mitigation in IEC 61850 power utility automation systems. The operational part is composed of engineering computers, supervision software, off-the-shelf intelligent relays (Intelligent Electronic Device-IED), a hardware-in-the-loop process simulation, and the cybersecurity tools include an attack generation station and a network analyzer. In this paper, we present the operational part, giving details on the power grid hardware-in-the-loop simulation and its importance in the understanding of cyber consequences on the global system. The article concludes giving preliminary experimental results showing consequences of a false data injection attack on a simple electrical architecture.
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