Secure impulsive synchronization control of multi-agent systems under deception attacks

TL;DR: This article investigates the Lyapunov stability problem for impulsive systems via event-triggered impulsive control, where dynamical systems evolve according to continuous-time equations most of the time, but occasionally exhibit instantaneous jumps when impulsive events are triggered.

TL;DR: In this article, the authors present a comprehensive survey on recent results on fault estimation, detection, diagnosis and fault-tolerant control of multi-agent systems, and cyber attack detection and secure control of MASs subject to two typical cyber attacks.

TL;DR: A secure communication scheme based on the quantized synchronization of master–slave neural networks under an event-triggered strategy is presented by combining the basic principle of cryptology and theoretical criteria are derived to ensure the bounded synchronization of Master– slave neural networks.

TL;DR: A survey on recent advances on security issues of industrial cyber-physical systems (ICPSs) is presented in this article, where two typical kinds of attacks, namely Denial-of-Service (DoS) attack and Deception attack, are discussed.

TL;DR: This work aims to understand how an enormous network of interacting dynamical systems — be they neurons, power stations or lasers — will behave collectively, given their individual dynamics and coupling architecture.

TL;DR: In this article, a new class of attacks, called false data injection attacks, against state estimation in electric power grids is presented and analyzed, under the assumption that the attacker can access the current power system configuration information and manipulate the measurements of meters at physically protected locations such as substations.

TL;DR: In this article, the authors reviewed some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006 and proposed several promising research directions along with some open problems that are deemed important for further investigations.

TL;DR: A new class of attacks, called false data injection attacks, against state estimation in electric power grids are presented, showing that an attacker can exploit the configuration of a power system to launch such attacks to successfully introduce arbitrary errors into certain state variables while bypassing existing techniques for bad measurement detection.