2 research outputs found
Sensor Fault Detection and Isolation via Networked Estimation: Full-Rank Dynamical Systems
This paper considers the problem of simultaneous sensor fault detection,
isolation, and networked estimation of linear full-rank dynamical systems. The
proposed networked estimation is a variant of single time-scale protocol and is
based on (i) consensus on \textit{a-priori} estimates and (ii) measurement
innovation. The necessary connectivity condition on the sensor network and
stabilizing block-diagonal gain matrix is derived based on our previous works.
Considering additive faults in the presence of system and measurement noise,
the estimation error at sensors is derived and proper residuals are defined for
fault detection. Unlike many works in the literature, no simplifying
upper-bound condition on the noise is considered and we assume Gaussian
system/measurement noise. A probabilistic threshold is then defined for fault
detection based on the estimation error covariance norm. Finally, a
graph-theoretic sensor replacement scenario is proposed to recover possible
loss of networked observability due to removing the faulty sensor. We examine
the proposed fault detection and isolation scheme on an illustrative academic
example to verify the results and make a comparison study with related
literature
Distributed control under compromised measurements:Resilient estimation, attack detection, and vehicle platooning
We study how to design a secure observer-based distributed controller such
that a group of vehicles can achieve accurate state estimates and formation
control even if the measurements of a subset of vehicle sensors are compromised
by a malicious attacker. We propose an architecture consisting of a resilient
observer, an attack detector, and an observer-based distributed controller. The
distributed detector is able to update three sets of vehicle sensors: the ones
surely under attack, surely attack-free, and suspected to be under attack. The
adaptive observer saturates the measurement innovation through a preset static
or time-varying threshold, such that the potentially compromised measurements
have limited influence on the estimation. Essential properties of the proposed
architecture include: 1) The detector is fault-free, and the attacked and
attack-free vehicle sensors can be identified in finite time; 2) The observer
guarantees both real-time error bounds and asymptotic error bounds, with
tighter bounds when more attacked or attack-free vehicle sensors are identified
by the detector; 3) The distributed controller ensures closed-loop stability.
The effectiveness of the proposed methods is evaluated through simulations by
an application to vehicle platooning