We consider a general multi-agent convex optimization problem where the agents are to collectively minimize global objective function subject inequality constraint, equality and constraint set. The is defined by sum of local functions, while set produced intersection sets. In particular, we study two cases: one absent, other sets identical. devise distributed primal-dual subgradient algorithms based on characterization optimal solutions as saddle points Lagrangian penalty functions. These...

This technical note studies a resilient control problem for discrete-time, linear time-invariant systems subject to state and input constraints. State measurements commands are transmitted over communication network could be corrupted by adversaries. In particular, we consider the replay attackers who maliciously repeat messages sent from operator actuator. We propose variation of receding-horizon law deal with attacks analyze resulting system performance degradation. A class competitive...

This paper gives three versions of the small gain theorem with restrictions for uncertain time-varying nonlinear systems.The result can be viewed as an extension time-invariant systems or without applied to study stabilization problem output regulation systems.

Inspired by current challenges in data-intensive and energy-limited sensor networks, we formulate a coverage optimization problem for mobile sensors as (constrained) repeated multiplayer game. Each tries to optimize its own while minimizing the processing/energy cost. The are subject informational restriction that environmental distribution function is unknown priori. We present two distributed learning algorithms where each only remembers utility values actions played during last plays....

We consider a multi-agent optimization problem where agents subject to local, intermittent interactions aim minimize sum of local objective functions global inequality constraint and state set. In contrast previous work, we do not require that the objective, functions, sets are convex. order deal with time-varying network topologies satisfying standard connectivity assumption, resort consensus algorithm techniques Lagrangian duality method. slightly relax requirement exact consensus, propose...

Moving Target Defense techniques have been proposed to increase uncertainty and apparent complexity for attackers. When more than one are effective limit opportunities of an attack, it is required compare these select the best defense choice. In this paper, we propose a three-layer model evaluate effectiveness different Defenses. This designed as attempt fill gap among existing evaluation methods works systematic framework comparison.

The Gannet Optimization Algorithm (GOA) has good performance, but there is still room for improvement in memory consumption and convergence. In this paper, an improved proposed to solve five engineering optimization problems. compact strategy enables the GOA save a large amount of memory, parallel communication allows algorithm avoid falling into local optimal solutions. We improve through combination strategy, we name Parallel Compact (PCGOA). performance study PCGOA on CEC2013 benchmark...

This paper studies a resilient control problem for discrete-time, linear time-invariant systems subject to state and input constraints. State measurements laws are transmitted over communication network could be corrupted by human adversaries. In particular, we consider class of adversaries, namely correlated jammers, who modeled as rational decision makers whose strategies highly the system operator. The coupled making process is two-level receding-horizon dynamic Stackelberg...

In this paper, we address the resilient state estimation problem for some relatively unexplored security issues cyber-physical systems, namely switching attacks and presence of stochastic process measurement noise signals, in addition to on actuator sensor signals. We model systems under attack as hidden mode switched linear with unknown inputs propose use multiple inference algorithm developed [1] tackle these issues. also furnish lacking asymptotic analysis. Moreover, characterize...

We introduce here a class of distributed quantized averaging algorithms for asynchronous communication networks with fixed and switching topologies. The focus this technical note is on the study convergence time proposed algorithms. By appealing to random walks graphs, we derive polynomial bounds expected presented, as function number agents in network.

In this article, we consider the problem of attack-resilient state estimation, that is, to reliably estimate true system states despite two classes attacks: (i) attacks on switching mechanisms and (ii) false data injection actuator sensor signals, in presence stochastic process measurement noise signals. We model systems under attack as hidden mode switched linear with unknown inputs propose use a multiple-model inference algorithm tackle these security issues. Moreover, characterize...

Mobile robots such as unmanned vehicles integrate heterogeneous capabilities in sensing, computation, and control. They are representative cyber-physical systems where the cyberspace physical world strongly coupled. However, safety of mobile is significantly threatened by cyber/physical attacks software/hardware failures. These threats can thwart normal robot operations cause misbehaviors. In this paper, we propose a novel anomaly detection system, which leverages dynamics to detect...

In this paper, we investigate a model where defender and an attacker simultaneously repeatedly adjust the defenses attacks. Under model, propose two iterative reinforcement learning algorithms which allow to identify optimal when information about is limited. With probability one, adaptive algorithm converges best response with respect attacks diminishingly explores system. arbitrarily close robust min-max strategy despite that persistently The convergence formally proven performance...

We consider a general multi-agent convex optimization problem where the agents are to collectively minimize global objective function subject inequality constraint, equality and constraint set. The is defined by sum of local functions, while set produced intersection sets. In particular, we study two cases: one absent, other sets identical. devise distributed primal-dual subgradient algorithms which based on characterization optimal solutions as saddle points Lagrangian penalty functions....