Coordination Control Of Multi-agent Systems Research Articles

Resilient interval observer-based coordination control for multi-agent systems under stealthy attacks

In this paper, the coordination control problem of multi-agent systems (MASs) subjected to stealthy attacks and uncertainties is considered, where the uncertainties refer to unknown external disturbances and initial states. We consider a scenario in which the sensors are maliciously attacked, rendering the traditional interval observer’s bounds ineffective for estimating the system states. By solving the linear programming problem, the maximum destructive attack sequences are generated. A distributed resilient interval observer composed of a resilient framer and a control protocol is designed, in which the construction of control protocol for each agent depends on the framer information of its own and its neighbors. It is demonstrated by the cooperativity theory and the Lyapunov stability theory that the distributed resilient interval observer can not only realize interval-valued state estimation for each agent but also drive the cooperative behavior of MASs. In addition, the observer gain matrix is selected and optimized by solving a semi-definite programming problem to provide tighter bounds for each agent. Meanwhile, the bounds of stealthy attacks are calculated. Finally, through a simulation example, the superiority of the distributed resilient interval observer and the effectiveness of the resilient interval observer-based consensus control algorithms are validated.

Group Hybrid Coordination Control of Multi-Agent Systems With Time-Delays and Additive Noises

A new kind of group coordination control problem-group hybrid coordination control is investigated in this paper. The group hybrid coordination control means that in a whole multi-agent system (MAS) that consists of two subgroups with communications between them, agents in the two subgroups achieve consensus and containment, respectively. For MASs with both time-delays and additive noises, two group control protocols are proposed to solve this problem for the containment-oriented case and consensus-oriented case, respectively. By developing a new analysis idea, some sufficient conditions and necessary conditions related to the communication intensity between the two sub-groups are obtained for the following two types of group hybrid coordination behavior: 1) Agents in one subgroup and in another subgroup achieve weak consensus and containment, respectively; 2) Agents in one subgroup and in another subgroup achieve strong consensus and containment, respectively. It is revealed that the decay of the communication impact between the two sub-groups is necessary for the consensus-oriented case. Finally, the validity of the group control results is verified by several simulation examples.

Game-based coordination control of multi-agent systems

In this paper, we are interested in how agents interact with each other in multi-agent systems. First, we model the interactions among agents in multi-agent systems as a multi-player game. The topology of the interactions among agents is a directed graph. We design cost functions for the game and assume that each agent in the systems tends to minimize its own cost. Then, the unique Nash equilibrium solution to the proposed multi-player game is obtained as the next state of the agent. A necessary and sufficient condition for achieving multi-agent consensus is established using the system transformation method and graph theory. Furthermore, we extend the result to the problem of containment control in the presence of leaders. The criterion for solving the containment control is also given in this paper. Finally, several simulation examples are given to verify the effectiveness of the theoretical results.

Interval Observer-Based Robust Coordination Control of Multi-Agent Systems Over Directed Networks

In this paper, the robust coordination control of multi-agent systems (MASs) with uncertainties is considered, where the uncertainties include the external disturbances and the measurement noises as well as the unknown initial states. Motivated by the interval observer of single-agent systems, a distributed interval observer is designed for MASs communicating through a directed network which contains a directed spanning tree by using only the bounding information on the uncertainties and the output information, to implement the interval-valued state estimation on the absolute state of each agent. It also finds that the robust coordination control is a by-part of the distributed interval observer design of this kind of MASs. Moreover, a time-invariant transformation is used to perfect the distributed interval observer design. Finally, numerical simulations are proposed to verify the theoretical results.

Distributed edge-based event-triggered coordination control for multi-agent systems

This paper studies edge-based event-triggered strategies for the average consensus problem in multi-agent systems. To this end, a distributed event-triggered algorithm is presented based on edge information rather than neighbor information, where positive minimum inter-event times are guaranteed between all communication links in the network. Moreover, the triggering mechanism is constructed in a fully distributed way which uses only relative state differences based on local neighborhood information without any global graph topology information. This treatment greatly reduces the communication frequency compared with continuous-time average consensus algorithms. We show that the proposed algorithm makes all agents converge to the average of their initial states asymptotically, and the positive minimum inter-event time for each link is controllable by two corresponding agents through their triggering parameters.

Containment control for multi-agent systems with fractional Brownian motion

The coordination control of multi-agent systems (MASs) with stochastic noise has been widely studied. But it is still unclear when the stochastic noise is the fractional Brownian motion (fBm), which has the character of memorability. In this paper, we investigate the containment control problem of MASs with fBm over a directed communication network. Firstly, we design several state observers to estimate the states of the followers. Then, based on the estimation information, we design a novel control function for each follower. With the aid of the properties of analytic semigroup and fixed point theorem, we prove that the MASs can achieve the mean-square containment control or quasi-containment control. Finally, we provide simulation examples to demonstrate the effectiveness of the obtained theoretical results.

Data-based optimal coordination control of continuous-time nonlinear multi-agent systems via adaptive dynamic programming method

This paper focuses on the optimal coordination control problem for continuous-time nonlinear multi-agent systems with completely unknown dynamics via a data-based distributed adaptive dynamic programming method. As for most real-world applications, accurate system models are complicated to obtain, which restricts the application of the conventional methods. Moreover, it is challenging to design optimal coordination control of multi-agent systems especially for the time-varying communication topology. To deal with the difficulties, we investigate a distributed adaptive dynamic programming method with identifier-critic architecture under the switching communication topology. First, using the available system data, an online adaptive identifier is developed to approximate the unknown model dynamics, and simultaneously a critic neural network is employed for approximation of the optimal cost function, which yields approximated optimal coordination control in real time. Then, we analyze the stability of our proposed scheme. Eventually, the simulation illustrates the effectiveness of the developed method.

Path tracking and coordination control of multi-agent systems: a robust tube-based MPC scheme

This paper addresses the reference tracking problem subject to formation constraints for a group of unmanned vehicles. A scheme based on receding horizon control ideas has been developed, whose the main feature consists in avoiding the need to explicitly impose non-convex constraints in the underlying optimization problem. The latter has been achieved by exploiting the properties provided by a novel description of the kinematic evolution when the agents are organized as a swarm. Numerical simulations on a team of five agents described by double integrator models are presented to show the effectiveness of the proposed control architecture.

Neighborhood Interval Observer Based Coordination Control for Multi-agent Systems with Disturbances

This paper focuses on multi-agent systems with uncertain disturbances, in which only the bounding functions on the disturbances and the bounds on the initial state of each agent are known. By designing a neighborhood interval observer for this kind of multi-agent system, the estimation of the sum of the relative state of each agent associated with itself and its neighbors is frstly realized. Then, on the basis of these estimated information, local control algorithm is designed to drive the system to achieve bounded consensus.

Event-triggered Coordination Control for Multi-agent Systems with Connectivity Preservation

This work investigates the connectivity preservation problem of multi-agent systems with event-triggered controllers. The agents in the system have only limited communication ranges, and they are required to achieve rendezvous while preserving the connectivity of the communication graph. To reduce the amount of communication packages, event-triggering mechanism is employed. We propose two kinds of event triggers to realize the connectivity-preserving rendezvous of the multi-agent system, i.e., the connectivity trigger to preserve the network connectivity, and the convergence trigger to drive the agents to achieve rendezvous. By introducing a particular constraint function in the controller design, the control inputs of the agents can be bounded throughout the rendezvous process. This guarantees that the controller can be physically implemented in practice. It is proven that the agent group will achieve rendezvous while all the existing communication links can be preserved under some very mild assumptions on the controller design. Moreover, Zeno behavior can be avoided by using an event/time hybrid triggering approach. The effectiveness of the proposed event-triggered control is illustrated by simulations.

Sampling-based self-triggered coordination control for multi-agent systems with application to distributed generators

ABSTRACTThis work investigates the coordination control problem for multiple distributed generation (DG) units with a hierarchical control structure. At the secondary control level, an event-triggered power sharing strategy based on the concept of multi-agent consensus has been proposed for the DG coordination control. Unlike existing consensus-based DG control approaches, the proposed control algorithm is based on sampled data. Thus the event triggering and controller updating actions can only be executed at the sampling time instants. To further reduce the amount of communication among DGs, the proposed event-triggered algorithm is extended to a self-triggered algorithm, where the inter-agent communication transmission is no longer required to be executed at each sampling time instant. The case study results show that the self-triggered algorithm can achieve nearly the same performance on DG coordination as that of the event-triggered algorithm, while significantly reduces the amount of communication.

Consensus Control for Vessel Traffic: the state of Arts and Prospects

With the rapid increase of port throughout, the number of vessels increases and the vessel traffic form become more complex. Therefore, how to realize the maximum utilization of limited navigation resources becomes one of the hottest issues. The consensus and coordination control of multi-agent systems could be adopted in the vessel traffic systems to improve the navigation efficiency and ensure safety in the water traffic. This paper reviews related work of the application of multi-agent system consensus control in the vessel traffic. In-depth analysis and discussion is made on swarming, distributed coordination control, consensus with external disturbances, and formation problems in the water traffic system. And also some challenging problems and prospects are presented.

Group controllability of discrete-time multi-agent systems

Controllability is a fundamental issue concerning control of multi-agent networks and a very important research topic in the modeling, analysis and coordination control of multi-agent systems. Group controllability problem is a further extension of the controllability problem of the general multi-agent systems, which mainly studies the cooperation and control of multi-agent systems with multiple sub-groups or multiple intelligence clusters. Comparing with the controllability of the general multi-agent systems, the group controllability is not only to consider the information interaction among the groups, but also to consider the information interaction between different groups, which makes the system reflect the effect of a whole and also the internal structure of the sub-groups. This paper addresses the group controllability problems of discrete-time multi-agent systems with time-delay, in which both switching topology and fixed topology are considered. This paper also proposes the general definition of the group controllability, as well as establishes group controllability criteria from the algebraic and graphical perspectives. Numerical examples and simulations are proposed to illustrate the theoretical results.

群平衡化赋权有向图/无向图的分布式算法研究

解决多智能体系统一致性协调控制的关键问题是设计合适的协议或算法使得多智能体的状态最终达到一致。己有的理论结果说明一些图平衡条件，如平衡条件和群平衡条件，是解决多智能体系统平均一致性问题和群平均一致性问题的一个必要条件。因此怎样平衡化和群平衡化一个一般图是一个值得研究的问题。然而目前涉及到如何平衡化和群平衡化一个一般图的结果还很少。本文针对有向拓扑图和无向拓扑图，分别提出两种不同的群平衡化算法，并从理论分析和数值仿真两方面验证两种算法的有效性。 A key problem of solving the consensus coordination control of multi-agent systems is to design appropriate protocols or algorithms which guarantee the agents reaching consensus. Although existing theoretical results have illustrated the balance conditions and the group-balance condi-tions are necessary when it comes to average consensus and group average consensus respectively, there are few results on how to balance and group-balance a general graph. In this paper, we design two distributed algorithm to group-balance directed and undirected graphs respectively, and prove the validity of the algorithms via both theoretical analysis and example illustrations.

Coordination control of multi-agent systems with second-order nonlinear dynamics using fully distributed adaptive iterative learning

This paper investigates the distributed coordination problem for leader–follower multi-agent systems with second-order nonlinear dynamics by using adaptive iterative learning control. It is assumed that the state information of the leader is only available to a portion of the follower agents and the bounded input of the leader is unavailable to any follower agent. Without using any global information, a fully distributed adaptive iterative learning protocol with distributed adaptive learning laws for the control gains is designed in this paper, under which consensus is reached for all undirected connected communication graph. Furthermore, as an extension of the former result, the formation problem is studied. Finally, simulation examples are given to illustrate the theoretical analysis.

Sliding mode coordination control for multiagent systems with underactuated agent dynamics

In this paper, we develop a new integrated coordinated control and obstacle avoidance approach for a general class of underactuated agents. We use graph-theoretic notions to characterise communication topology in the network of underactuated agents as determined by the information flow directions and captured by the graph Laplacian matrix. Obstacle avoidance is achieved by surrounding the stationary as well as moving obstacles by elliptical or other convex shapes that serve as stable periodic solutions to planar systems of ordinary differential equations and using transient trajectories of those systems to navigate the agents around the obstacles. Decentralised controllers for individual agents are designed using sliding mode control approach and are only based on data communicated from the neighbouring agents. We demonstrate the efficacy of our theoretical approach using an example of a system of wheeled mobile robots that reach and maintain a desired formation. Finally, we validate our results experimentally.

Interval consensus problem of multi-agent systems in accordance with switching protocol

In this paper, we discuss the interval consensus problem of multi-agent systems by providing a special Laplacian of directed graphs. As one of the most important issues in the coordination control of multi-agent systems, the consensus problem requires that the output of several spatially distributed agents reach a common value that depends on the states of all agents. For the given consensus protocol and initial states, a fixed consensus value is obtained. The resulting consensus value, however, may not be ideal or meet the quality that we require from the multi-agent system. In this paper, by introducing two state-dependent switching parameters into the consensus protocol, the system given by the proposed protocol can globally asymptotically converge to a designated point on a special closed and bounded interval. In other words, the system given by the proposed protocol can globally asymptotically reach interval consensus and then the system can also achieve a generalised interval average consensus if the directed graph is balanced. Simulations are presented to demonstrate the effectiveness of our theoretical results.

Coordination of multiagents interacting under independent position and velocity topologies.

We consider the coordination control for multiagent systems in a very general framework where the position and velocity interactions among agents are modeled by independent graphs. Different algorithms are proposed and analyzed for different settings, including the case without leaders and the case with a virtual leader under fixed position and velocity interaction topologies, as well as the case with a group velocity reference signal under switching velocity interaction. It is finally shown that the proposed algorithms are feasible in achieving the desired coordination behavior provided the interaction topologies satisfy the weakest possible connectivity conditions. Such conditions relate only to the structure of the interactions among agents while irrelevant to their magnitudes and thus are easy to verify. Rigorous convergence analysis is preformed based on a combined use of tools from algebraic graph theory, matrix analysis as well as the Lyapunov stability theory.

Adaptive Coordination Control of Multi-Agent Systems with Switching Topologies and Unknown Nonlinear Dynamics

In this paper, we study the leader-following adaptive consensus problem for multi-agent systems with unknown nonlinear dynamics. The topologies of the networks are switching. A novel adaptive consensus algorithm is proposed by using linear parameterizations of unknown nonlinear dynamics of all agents. By stability analysis and parameter convergence analysis of the proposed algorithm, adaptive consensus can be realized based on neighboring graphs. The stability analysis is based on algebraic graph theory and Lyapunov theory, the PE condition plays a key role in parameter convergence analysis. Example is given to validate the theoretical results.

Distributed Coordination Control of Multiagent Systems While Preserving Connectedness

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> This paper addresses the connectedness issue in multiagent coordination, i.e., the problem of ensuring that a group of mobile agents stays connected while achieving some performance objective. In particular, we study the rendezvous and the formation control problems over dynamic interaction graphs, and by adding appropriate weights to the edges in the graphs, we guarantee that the graphs stay connected. </para>