Decentralized Event-Triggered Average Consensus for Multi-Agent Systems in CPSs with Communication Constraints

The paper investigates decentralized event-triggered average consensus problem for multi-agent systems in cyberphysical systems(CPSs) with communication constraints.To reduce communication burden and improve the communication efficiency of multi-agent systems in CPSs,event-trigger is distributed at subsystem/agent level.A multi-agent system is then modeled as a reduced dimension hybrid system by taking into account decentralized event-triggered mechanism,communication delays and data dropouts within one framework.Some sufflcient conditions for average consensus of each agent and an upper bound of communication delay and maximal allowable number of successive data dropouts(MANSD) are obtained,which can conveniently provide the relationship between the triggering parameters,communication constraints and the system stability.Specially,the quantitative relationship between the triggering parameters,MANSD and the system stability is derived.Finally,simulation results are given to illustrate the effectiveness of the proposed method.

Coalition Formation for Multiple UAVs Cooperative Search and Attack with Communication Constraints in Unknown Environment

A coalition formation algorithm is presented with limited communication ranges and delays in unknown environment,for the performance of multiple heterogeneous unmanned aerial vehicles(UAVs)in cooperative search and attack missions.The mathematic model of coalition formation is built on basis of the minimum attacking time and the minimum coalition size with satisfying resources and simultaneous strikes requirements.A communication protocol based on maximum number of hops is developed to determine the potential coalition members in dynamic network.A multistage sub-optimal coalition formation algorithm(MSOCFA)with polynomial time is established.The performances of MSOCFA and particle swarm optimization(PSO)algorithms are compared in terms of complexity,mission performance and computational time.A complex scenario is deployed to illustrate how the coalitions are formed and validate the feasibility of the MSOCFA.The effect of communication constraints(hop delay and max-hops)on mission performance is studied.The results show that it is beneficial to determine potential coalition members in a wide and deep range over the network in the presence of less delay.However,when the delays are significant,it is more advantageous to determine coalitions from among the immediate neighbors.

Nonlinear Filtering With Sample-Based Approximation Under Constrained Communication:Progress, Insights and Trends

The nonlinear filtering problem has enduringly been an active research topic in both academia and industry due to its ever-growing theoretical importance and practical significance.The main objective of nonlinear filtering is to infer the states of a nonlinear dynamical system of interest based on the available noisy measurements. In recent years, the advance of network communication technology has not only popularized the networked systems with apparent advantages in terms of installation,cost and maintenance, but also brought about a series of challenges to the design of nonlinear filtering algorithms, among which the communication constraint has been recognized as a dominating concern. In this context, a great number of investigations have been launched towards the networked nonlinear filtering problem with communication constraints, and many samplebased nonlinear filters have been developed to deal with the highly nonlinear and/or non-Gaussian scenarios. The aim of this paper is to provide a timely survey about the recent advances on the sample-based networked nonlinear filtering problem from the perspective of communication constraints. More specifically, we first review three important families of sample-based filtering methods known as the unscented Kalman filter, particle filter,and maximum correntropy filter. Then, the latest developments are surveyed with stress on the topics regarding incomplete/imperfect information, limited resources and cyber security.Finally, several challenges and open problems are highlighted to shed some lights on the possible trends of future research in this realm.

Distributed cooperative localization for sparse communication network with multi-locating messages

In cooperative localization with sparse communication networks, an agent maybe only receives part of locating messages from the others. It is difficult for the receiver to utilize the part instead of global knowledge. Under the extended Kalman filtering, the utilization of the locating message is maximized by two aspects： the locating message generating and multi-locating messages fusing. For the former, the covariance upper-bound technique, by introducing amplification coefficients, is employed to remove the dependency of locating messages on the global knowledge. For the latter, an optimization model is setup; the covariance matrix determinant of the receiver＇s state estimate, expressed as a function of the amplification coefficients, is selected as the optimization criterion, under linear constraints on the amplification coefficient characteristics and the communication connectivity. Using the optimization solution, the local optimal state of the receiver agent is obtained by the weighting fusion. Simulation with seven agents is shown to evaluate the effectiveness of the proposed algorithm.

Application of wireless sensor networks to aircraft control and health management systems

Use of fly-by-wire technology for aircraft flight controls have resulted in an improved performance and reliability along with achieving reduction in control system weight. Implementation of full authority digital engine control has also resulted in more intelligent, reliable, light-weight aircraft engine control systems. Greater reduction in weight can be achieved by replacing the wire harness with a wireless communication network. The first step towards fly-by-wireless control systems is likely to be the introduction of wireless sensor networks (WSNs). WSNs are already finding a variety of applications for both safety-critical and nonsafety critical distributed systems. Some of the many potential benefits of using WSN for aircraft systems include weight reduction, ease of maintenance and an increased monitoring capability. This paper discusses the application of WSN for several aircraft systems such as distributed aircraft engine control, aircraft flight control, aircraft engine and structural health monitoring systems. A brief description of each system is presented along with a discussion on the technological challenges. Future research directions for application of WSN in aircraft systems are also discussed.