This paper addresses the distributed formation control problem of a networked multi-agent system (MAS) subject to limited communication resources. First, a dynamic event-triggered communication mechanism (DECM) is developed to schedule inter-agent communication such that some unnecessary data exchanges among agents can be reduced so as to achieve better resource efficiency. Different from most of the existing event-triggered communication mechanisms, wherein threshold parameters are fixed all the time, the threshold parameter in the developed event triggering condition is dynamically adjustable in accordance with a dynamic rule. It is numerically shown that the proposed DECM can achieve a better tradeoff between reducing inter-agent communication frequency and preserving an expected formation than some existing ones. Second, an event-triggered formation protocol is delicately proposed by using only locally triggered sampled data in a distributed manner. Based on the formation protocol, it is shown that the state formation control problem is cast into an asymptotic stability problem of a reduced-order closed-loop system. Then, criteria for designing desired formation protocol and communication mechanism are derived. Finally, the effectiveness and advantages of the proposed approach are demonstrated through a comparative study in multirobot formation control.

Distributed Formation Control of Networked Multi-Agent Systems Using a Dynamic Event-Triggered Communication Mechanism

A networked control system (NCS) is a control system which involves a communication network. In NCSs, the continuous-time measurement is usually sampled and quantized before transmission. Then, the measurement is transmitted to the remote controller via the communication channel, during which the signal may be delayed, lost or even sometimes not allowed for transmission due to the communication or energy constraints. In recent years, the modeling, analysis and synthesis of networked control systems (NCSs) have received great attention, which leads to a large number of publications. This paper attempts to present an overview of recent advances and unify them in a framework of network-induced issues such as signal sampling, data quantization, communication delay, packet dropouts, medium access constraints, channel fading and power constraint, and present respective solution approaches to each of these issues. We draw some conclusions and highlight future research directions in end.

Analysis and synthesis of networked control systems: A survey of recent advances and challenges.

This paper is concerned with the guaranteed cost control problem for a class of Markov jump discrete-time neural networks (NNs) with event-triggered mechanism, asynchronous jumping, and fading channels. The Markov jump NNs are introduced to be close to reality, where the modes of the NNs and guaranteed cost controller are determined by two mutually independent Markov chains. The asynchronous phenomenon is considered, which increases the difficulty of designing required mode-dependent controller. The event-triggered mechanism is designed by comparing the relative measurement error with the last triggered state at the process of data transmission, which is used to eliminate dispensable transmission and reduce the networked energy consumption. In addition, the signal fading is considered for the effect of signal reflection and shadow in wireless networks, which is modeled by the novel Rice fading models. Some novel sufficient conditions are obtained to guarantee that the closed-loop system reaches a specified cost value under the designed jumping state feedback control law in terms of linear matrix inequalities. Finally, some simulation results are provided to illustrate the effectiveness of the proposed method.

Event-Triggered Asynchronous Guaranteed Cost Control for Markov Jump Discrete-Time Neural Networks With Distributed Delay and Channel Fading

This paper is concerned with the problem of distributed $H_{\infty }$ filtering for a cloud-aided active semi-vehicle suspension system. The information of semi-vehicle suspension system are transmitted to the cloud through wireless network with some unreliable characteristics, such as communication time-delay and limited bandwidth, which are solved by the delay-distribution dependent method and event-triggered scheme, respectively. In order to reduce the dimensions of results, the semi-vehicle suspension is decomposed into two interconnected subsystems. At the side of remote cloud, filters are designed for each subsystem with considering the unreliable characteristics of network and stochastic sensor faults, simultaneously. A codesign algorithm is provided to obtain the distributed $H_\infty$ filtering and the event-triggered scheme, simultaneously. Finally, the efficient performances of the codesigned algorithm are evaluated both in time and frequency domains under different road conditions.

Codesign of Event-Triggered and Distributed $H_{\infty }$ Filtering for Active Semi-Vehicle Suspension Systems

In this paper, the distributed ${H_{\infty }}$ state estimation problem is investigated for a class of filtering networks with time-varying switching topologies and packet losses. In the filter design, the time-varying switching topologies, partial information exchange between filters, the packet losses in transmission from the neighbor filters and the channel noises are simultaneously considered. The considered topology evolves not only over time, but also by event switches which are assumed to be subjects to a nonhomogeneous Markov chain, and its probability transition matrix is time-varying. Some novel sufficient conditions are obtained for ensuring the exponential stability in mean square and the switching topology-dependent filters are derived such that an optimal ${H_{\infty }}$ disturbance rejection attenuation level can be guaranteed for the estimation disagreement of the filtering network. Finally, simulation examples are provided to demonstrate the effectiveness of the theoretical results.

Distributed $H_\infty$ State Estimation for a Class of Filtering Networks With Time-Varying Switching Topologies and Packet Losses

This paper is concerned with the problem of vertical attitude estimation of a two-degree-of-freedom quarter-car suspension system by designing a distributed filtering network, where several distributed filters estimate vehicle heave motion cooperatively under consideration of external disturbance, network channel noises, and measurement error. The sampled data are transmitted through wireless networks. In order to reduce network traffic load and save communication resources, a novel periodic event-triggered sampling scheme is proposed, under which data are transmitted only when the proposed triggering condition is violated. Codesign of event-triggered and distributed filters is derived to guarantee well $H_{\infty }$ robustness to the system noises considered above. Finally, the experiments are given to show the effectiveness of the proposed filtering system.

Event-Based Distributed $H_{\infty }$ Filtering Networks of 2-DOF Quarter-Car Suspension Systems

The problem of observer-based decentralized event-triggered H ∞ control for networked systems is investigated in this paper. The system measurements and control inputs are grouped into several nodes. An event-triggered transmission scheme is introduced to choose those necessary signals to be transmitted from the plant to the observer and from the controller to the actuator, where signals from control input nodes and from measurement nodes are released not necessarily synchronously. Under the decentralized event-triggered transmission scheme, H ∞ performance analysis for the resultant closed-loop system is made, and an algorithm to designing suitable observers and controllers is presented as well. Moreover, a sufficient condition is derived such that the inter-event time is strictly greater than zero. Finally, two examples are given to show the effectiveness of the method proposed in this paper.

Qianqian Hong

Papers

Event-Based Distributed $H_{\infty }$ Filtering Networks of 2-DOF Quarter-Car Suspension Systems

Observer-based decentralized event-triggered H∞ control for networked systems