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

TL;DR

This paper introduces a sound and complete fault detection method for cyber-physical systems using model invalidation and MILP, enabling efficient, guaranteed detection with receding horizon implementation.

Contribution

It develops a novel set-membership fault detection approach for hidden-mode switched affine models, incorporating T-detectability and weak-detectability concepts for improved robustness.

Findings

The approach is sound and complete for fault detection.

Fault detection reduces to MILP feasibility problems.

Numerical examples demonstrate efficiency in smart building systems.

Abstract

This paper presents a sound and complete fault detection approach for cyber-physical systems represented by hidden-mode switched affine models with time varying parametric uncertainty. The fault detection approach builds upon techniques from model invalidation. In particular, a set-membership approach is taken where the noisy input-output data is compared to the set of behaviors of a nominal model. As we show, this set-membership check can be reduced to the feasibility of a mixed-integer linear programming (MILP) problem, which can be solved efficiently by leveraging the state-of-the-art MILP solvers. In the second part of the paper, given a system model and a fault model, the concept of T-detectability is introduced. If a pair of system and fault models satisfies T-detectability property for a finite T, this allows the model invalidation algorithm to be implemented in a receding horizon manner, without compromising detection guarantees. In addition, the concept of weak-detectability is introduced which extends the proposed approach to a more expressive class of fault models that capture language constraints on the mode sequences. Finally, the efficiency of the approach is illustrated with numerical examples motivated by smart building radiant systems.