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Robust Resilient Signal Reconstruction under Adversarial Attacks

We consider the problem of signal reconstruction for a system under sparse signal corruption by a malicious agent. The reconstruction problem follows the standard error coding problem that has been studied extensively in the literature. We include a …

Large-Scale Resilient Collaborative Machine Learning

The past few decades have seen a tremendous increase in the volume and complexity of data generated in scientific discovery processes. Moreover, due to the rapid growth in internet and networking technology, it is now common for these experiments to …

Model and Load Predictive Control for Design and Energy Management of Shipboard Power Systems

In current Medium Voltage DC (MVDC) Shipboard Power Systems (SPSs), multiple sources exist to supply power to a common dc bus. Conventionally, the power management of such systems is performed by controlling Power Generation Modules (PGMs) which …

Degradation Aware Predictive Energy Management Strategy for Ship Power Systems

Integration of modern defence weapons into ship power systems poses a challenge in terms of meeting the high ramp rate requirements of those loads. It might be demanding for the generators to meet the ramp rates of these loads. Failure to meet so, …

Low-bandwidth Modular Mathematical Modeling of DC Microgrid Systems for Control Development with Application to Shipboard Power Systems

In recent years, DC and AC microgrid (MG) systems have attracted a major attention due to various potential for integration of future technology into conventional systems and control. The integration of such technology requires appropriate tools for …

Attack-Resilient Weighted L1 Observer with Prior Pruning

This paper proposed a weighted L1 observer with prior pruning scheme against FDIAs. The pruning method gives a method to improve localization precision of any underlying localization algorithm withot training effort. Moreover, the weighted L1 observer with prior pruning is capable of coping with high-percentage of attacks among measurement nodes, which relaxes the transitional restriction on the maximum attack percentage for resilient L1 observer, thereby improve the resiliency of systems.

Robust Control for a Class of Nonlinearly Coupled Hierarchical Systems with Actuator Faults

This paper proposes an approach to addresses the control challenges posed by a fault-induced uncertainty in both the dynamics and control input effectiveness of a class of hierarchical nonlinear systems in which the high-level dynamics is nonlinearly …

Attack-Resilient Observer Pruning for Path-Tracking Control of Wheeled Mobile Robot

In this paper, an attack-resilient path tracking control scheme for wheeled mobile robot under an optimization-based FDIA was designed. The main contributions include; (1) Stable path-tracking control system for DDWMR, (2) Optimizationbased FDIA for DDWMR, and (3) The pruning-based observer design using UKF as the underlying observer. It was shown that the proposed pruning-based observer significantly improves the signal-to-attack ratio such that the UKF is able to resiliently estimate the state of the DDWMR even when portion of the sensor measurements were subject to an FDIA.

Multi-Model Resilient Observer under False Data Injection Attacks

In this paper, we present the concept of boosting the resiliency of optimization-based observers for cyber-physical systems (CPS) using auxiliary sources of information. Due to the tight coupling of physics, communication and computation, a malicious …

Evasion attacks with adversarial deep learning against power system state estimation

Cyberattacks against critical infrastructures, including power systems, are increasing rapidly. False Data Injection Attacks (FDIAs) are among the attacks that have been demonstrated to be effective and have been getting more attention over the last …