Towards Distributed Accommodation of Covert Attacks in Interconnected Systems

The problem of mitigating maliciously injected signals in interconnected systems is dealt with in this paper. We consider the class of covert attacks, as they are stealthy and cannot be detected by conventional means in centralized settings. Distributed architectures can be leveraged for revealing such stealthy attacks by exploiting communication and local model knowledge. We show how such detection schemes can be improved to estimate the action of an attacker and we propose an accommodation scheme in order to mitigate or neutralize abnormal behavior of a system under attack

Fault Detection and Isolation of Nonlinear Systems with Generalized Hamiltonian Representation

The problem of fault diagnosis in a class of nonlinear system is considered. Systems that can be written in the so‐called Generalized Hamiltonian Representation (which is equivalent to an Euler‐Lagrange representation) are studied, and a model‐based observer approach for this class of systems is developed. The main advantage of the proposed approach is the facility to design the required observers, which take advantage of the system structure given by the Hamitonian representation. In order to show the proposed schema, a model of a permanent magnet synchronous machine is revised and the fault diagnosis schema presented. Simulation results confirm the effectivity of the proposed schema

Toward robust visual odometry using prior 2D map information and multiple hypothesis particle filtering

Visual odometry can be used to estimate the pose of a robot from current and recent video frames. A problem with these methods is that they drift over time due to the accumulation of estimation errors at each time-step. In this short paper we propose and briefly demonstrate the potential benefit of using prior 2D, top-down map information combined with multiple hypothesis particle filtering to correct visual odometry estimates. The results demonstrate a substantial improvement in robustness and accuracy over the sole use of visual odometry

Root Cause Analysis of Actuator Fault

This chapter develops a two-level fault diagnosis (FD) and root cause analysis (RCA) scheme for a class of interconnected invertible dynamic systems and aims at detecting and identifying actuator fault and the causes. By considering actuator as an individual dynamic subsystem connected with process dynamic subsystem in cascade, an interconnected system is then constituted. Invertibility of the interconnected system in faulty model is studied. An interconnected observer is introduced and aims at monitoring the performance of the interconnected system and providing information of actuator fault occurrence. A local fault filter algorithm is then triggered to identify the root causes of the detected actuator faults. According to real plant, outputs of the actuator subsystem are assumed inaccessible and are reconstructed by measurements of the global system, thus providing a means for monitoring and diagnosing the plant at both local and global level

The challenge of advanced model-based fdir techniques for aerospace systems: the 2011 situation

For aerospace systems, advanced model-based Fault Detection, Identification, and Recovery (FDIR) challenges range from predesign and design stages for upcoming and new programs up to the improvement of the performance of in-service flying systems. However, today, their application to real aerospace world has remained extremely limited. The paper underlines the reasons for a widening gap between the advanced scientific FDIR methods being developed by the academic community and technological solutions demanded by the aerospace industry