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This paper presents a sound and complete fault detection approach forcyber-physical systems represented by hidden-mode switched affine models withtime varying parametric uncertainty. The fault detection approach builds upontechniques from model invalidation. In particular, a set-membership approach istaken where the noisy input-output data is compared to the set of behaviors ofa nominal model. As we show, this set-membership check can be reduced to thefeasibility of a mixed-integer linear programming (MILP) problem, which can besolved efficiently by leveraging the state-of-the-art MILP solvers. In thesecond part of the paper, given a system model and a fault model, the conceptof T-detectability is introduced. If a pair of system and fault modelssatisfies T-detectability property for a finite T, this allows the modelinvalidation algorithm to be implemented in a receding horizon manner, withoutcompromising detection guarantees. In addition, the concept ofweak-detectability is introduced which extends the proposed approach to a moreexpressive class of fault models that capture language constraints on the modesequences. Finally, the efficiency of the approach is illustrated withnumerical examples motivated by smart building radiant systems.

Guaranteed Model-Based Fault Detection in Cyber-Physical Systems: A Model Invalidation Approach