Observer-based event-triggered leader-following control of a class of linear multi-agent systems

This paper addresses an observer-based consensus problem for leader-following control of a class of linear multi-agent systems (MASs) under a directed communication topology via event-triggered approaches. State observers are employed to tackle the scenario wherein inner information of the follower agents are not available for measurement. And then, an observer-based distributed leader-following control scheme is developed on the basis of event-triggered mechanisms. Further, to avoid continuous measurement information monitor, we present a technical approach for generation of the combinational information from their own neighbouring agents only at triggered instants. In theory, the stability of the resulting closed-loop system is rigorously investigated, and it is proven that all signals in the closed-loop system are bounded and Zeno behaviour is also excluded. Finally, simulation examples are presented for illustration of the theoretical claims.     

分布式事件触发多自主体领导跟随一致性研究

为了提高系统的通信效率和能源利用率,减少多自主体系统硬件资源的浪费,提出了只需要自主体自身及其最近邻居节点信息的分布式事件触发控制算法。研究了带有动态领导者的二阶多自主体系统领导跟随一致性问题。应用矩阵论和现代控制理论研究了在分布式事件触发机制下的二阶系统,得到了基于事件触发机制的多自主体系统协同运动的收敛条件。通过理论分析与计算表明,在此控制协议下不会存在芝诺行为,并且多自主体系统可以实现领导跟随一致性。最后,应用计算机仿真验证了本文所提控制协议的可靠性。     

Distributed control of multi-agent systems over unknown communication networks using extremum seeking

In this paper, the solution of large-scale real-time optimization problems of multi-agent systems (MAS) is tackled in a distributed and a cooperative manner without the requirement of exact knowledge of network connectivity. Each agent in the communication network measures a local disagreement cost in addition to its local cost. The agents must work collaboratively to ensure that the system's unknown overall cost (i.e., the sum of the local cost of all the agents) is minimized. In order to minimize this cost, the local disagreement cost of all the agents must first be minimized. This minimization requires the solution of a consensus estimation problem and ensures that the agents reach agreement on their decision variables. To address this challenging problem, a distributed proportional-integral extremum seeking control technique is proposed, one that solves both problems simultaneously. Three simulation examples are included, they demonstrate the effectiveness and robustness of the proposed technique.     

Tracking control for multi-agent consensus with an active leader and variable topology

In this paper, we consider a multi-agent consensus problem with an active leader and variable interconnection topology. The state of the considered leader not only keeps changing but also may not be measured. To track such a leader, a neighbor-based local controller together with a neighbor-based state-estimation rule is given for each autonomous agent. Then we prove that, with the proposed control scheme, each agent can follow the leader if the (acceleration) input of the active leader is known, and the tracking error is estimated if the input of the leader is unknown.     

Coordination of multi-agent systems under switching topologies via disturbance observer-based approach

In this paper, a leader-following coordination problem of heterogeneous multi-agent systems is considered under switching topologies where each agent is subject to some local (unbounded) disturbances. While these unknown disturbances may disrupt the performance of agents, a disturbance observer-based approach is employed to estimate and reject them. Varying communication topologies are also taken into consideration, and their byproduct difficulties are overcome by using common Lyapunov function techniques. According to the available information in difference cases, two disturbance observer-based protocols are proposed to solve this problem. Their effectiveness is verified by simulations.     

Distributed robust consensus control of multi-agent systems with heterogeneous matching uncertainties

This paper considers the distributed consensus problem of linear multi-agent systems subject to different matching uncertainties for both the cases without and with a leader of bounded unknown control input. Due to the existence of nonidentical uncertainties, the multi-agent systems discussed in this paper are essentially heterogeneous. For the case where the communication graph is undirected and connected, based on the local state information of neighboring agents, a fully distributed continuous adaptive consensus protocol is designed, under which the consensus error is uniformly ultimately bounded and exponentially converges to a small adjustable bounded set. For the case where there exists a leader whose control input is unknown and bounded, a distributed adaptive consensus protocol is proposed to ensure the boundedness of the consensus error. A sufficient condition for the existence of the proposed protocols is that each agent is stabilizable.     

Consensus control of leader-following nonlinear multi-agent systems with distributed adaptive iterative learning control

This paper addresses the consensus problem of leader-following nonlinear multi-agent systems with iterative learning control. The assumption that only a small portion of following agents can receive the information of leader agent is considered. To approximate the nonlinear dynamics of a given system, the radial basis function neural network is introduced. Then, a distributed adaptive iterative learning control protocol with an auxiliary control term is designed, where the estimates of nonlinear dynamics are applied in control protocol design and three adaptive laws are presented. Furthermore, the convergence of the proposed control protocol is analysed by Lyapunov stability theory. Finally, a simulation example is provided to demonstrate the validity of theoretical results.     

Observer-based leader-following tracking control under both fixed and switching topologies

This paper studies the tracking problem for a class of leader-follower multi-agent systems moving on the plane using observerbased cooperative control strategies. In our set-up, only a subset of the followers can obtain some relative information on the leader. We assume that the control input of the leader is not known to any of the followers while the system matrix is broadcast to all the followers. To track such a leader, an observer-based decentralized feedback controller is designed for each follower and detailed analysis for the convergence is presented for both fixed and switching interaction topologies between agents with the method of common Lyapunov function. We can also generalize the result to the higher dimension case for fixed topology and some special system matrices of the leader for switching topology.     

Finite-time consensus control for second-order multi-agent systems without velocity measurements

This paper investigates the finite-time consensus problem for second-order multi-agent systems with unknown velocities and disturbances. By introducing the second-order sliding mode observer, two novel distributed finite-time protocols with only relative position measurements are proposed for the both cases with known and unknown boundaries of disturbances. On the basis of Lyapunov stability theorem and homogeneous theory, it is proved that the consensus can be achieved in finite time. Simulation examples are provided to show the effectiveness of the theoretical results.     

Distributed learning and cooperative control for multi-agent systems

This paper presents an algorithm and analysis of distributed learning and cooperative control for a multi-agent system so that a global goal of the overall system can be achieved by locally acting agents. We consider a resource-constrained multi-agent system, in which each agent has limited capabilities in terms of sensing, computation, and communication. The proposed algorithm is executed by each agent independently to estimate an unknown field of interest from noisy measurements and to coordinate multiple agents in a distributed manner to discover peaks of the unknown field. Each mobile agent maintains its own local estimate of the field and updates the estimate using collective measurements from itself and nearby agents. Each agent then moves towards peaks of the field using the gradient of its estimated field while avoiding collision and maintaining communication connectivity. The proposed algorithm is based on a recursive spatial estimation of an unknown field. We show that the closed-loop dynamics of the proposed multi-agent system can be transformed into a form of a stochastic approximation algorithm and prove its convergence using Ljung’s ordinary differential equation (ODE) approach. We also present extensive simulation results supporting our theoretical results.     

多智能体系统的有限时间包含控制研究

在固定有向拓扑结构下,研究了具有多个静态或动态领导者的多智能体有限时间包含控制问题;假设领导者之间不存在信息的交互,提出基于快速终端滑模的控制算法,该算法驱使跟随者的运动轨迹在有限时间收敛到由领导者组成的凸包中;进一步,考虑实际应用中跟随者状态不能在线获得的情况,提出基于有限时间观测器的包含控制协议;利用图论和Lyapunov有限时间稳定性理论,给出了有限时间包含控制的充分条件;最后通过仿真示例,验证了算法的有效性.     

Adaptive tracking control of leader-following linear multi-agent systems with external disturbances

In this paper, the consensus problem for leader-following linear multi-agent systems with external disturbances is investigated. Brownian motions are used to describe exogenous disturbances. A distributed tracking controller based on Riccati inequalities with an adaptive law for adjusting coupling weights between neighbouring agents is designed for leader-following multi-agent systems under fixed and switching topologies. In traditional distributed static controllers, the coupling weights depend on the communication graph. However, coupling weights associated with the feedback gain matrix in our method are updated by state errors between neighbouring agents. We further present the stability analysis of leader-following multi-agent systems with stochastic disturbances under switching topology. Most traditional literature requires the graph to be connected all the time, while the communication graph is only assumed to be jointly connected in this paper. The design technique is based on Riccati inequalities and algebraic graph theory. Finally, simulations are given to show the validity of our method.     

Decentralized adaptive awareness coverage control for multi-agent networks

In this paper a novel problem of adaptive awareness coverage is formulated. We model the mission domain using a density function which characterizes the importance of each point and is unknown beforehand. The desired awareness coverage level over the mission domain is defined as a non-decreasing differentiable function of the density distribution. A decentralized adaptive control strategy is developed to accomplish the awareness coverage task and learning task simultaneously. The proposed control law is memoryless and can guarantee the achievement of satisfactory awareness coverage of the mission domain in finite time with the approximation error of the density function converging to zero.     

The leader-following attitude control of multiple rigid spacecraft systems

In this paper, we consider the leader-following consensus problem for a multiple rigid spacecraft system whose attitude is represented by the unit quaternion. Most results on this problem rely on the assumption that every follower can access the state of the leader and are obtained via a decentralized control manner. By developing a nonlinear distributed observer for the leader system, we can solve this problem via a distributed control scheme under the mild assumptions that the state of the leader can reach every follower through a path and that the communication between followers is bidirectional. Moreover, our result can accommodate a class of desired angular velocities generated by a marginally stable linear autonomous system.     

A new framework of consensus protocol design for complex multi-agent systems

This paper aims to find a simple but efficient method for consensus protocol design. This paper presents two consensus protocols to solve the consensus problem of complex multi-agent systems that consist of inhomogeneous subsystems. The limitations of current studies are analyzed, and a novel model based on transfer functions is presented. This model can be used to describe both homogeneous and inhomogeneous multi-agent systems in a unified framework. Based on this model, two sufficient and necessary conditions for the consensus of complex multi-agent systems have been obtained. One is for the systems without any external input, and the other is for the systems with the same external input. Then, two corresponding distributed consensus protocols are presented. Considering that the complex multi-agent systems may require different outputs sometimes, the relationship between inputs and outputs is analyzed. Finally, some simulations are given to demonstrate the performance and effectiveness of the proposed approaches.     

Finite-time observers for multi-agent systems without velocity measurements and with input saturations

This paper is devoted to the distributed finite-time observers for multi-agent systems, where the control inputs are required to be bounded and the velocities are assumed to be not available for feedback. An effective framework through defining a class of coordinated saturation functions is introduced, under which both a first-order finite-time observer and a high-order finite-time observer are constructed. By applying the homogeneous theory for stability analysis, it is proven that all the states of the followers can converge to that of the leader in finite time under our proposed observers. With mild modifications of our control strategies, the foregoing results are then extended to the distributed finite-time containment control problem, where the states of the followers converge to the convex hull spanned by the multiple dynamic leaders. Numerical simulations are presented to demonstrate the efficiency of our methods.     

Adaptive finite-time consensus in multi-agent networks

This paper is concerned with the finite-time consensus problem of distributed agents having non-identical unknown nonlinear dynamics, to a leader agent that also has unknown nonlinear control input signal. By parameterization of unknown nonlinear dynamics, a Lyapunov technique in conjunction with homogeneity technique is presented for designing a decentralized adaptive finite-time consensus control protocol in undirected networks. Homogeneous Lyapunov functions and homogeneous vector fields are introduced in the stability analysis although the whole system is not homogeneous. Theoretical analysis shows that leader-following consensus can be achieved in finite-time, meanwhile, finite-time parameter convergence can be also guaranteed under the proposed control scheme. An example is given to validate the theoretical results.     

Adaptive coordinated tracking of multi-agent systems with quantized information

In this paper, we study the adaptive coordinated tracking problem for continuous-time first-order integrator systems with quantized information under switching undirected and fixed directed communication graphs, respectively. The combined effect of quantized relative information error and quantized absolute information error on the tracking result is investigated. Both the logarithmic quantizers and uniform quantizers are considered. It is shown that when logarithmic quantizers are used, exact coordinated tracking can still be achieved by properly choosing the design parameters in the controller while when uniform quantizers are used, practical coordinated tracking can be achieved with tracking error bounds proportional to the quantizer parameter. Simulation examples are provided to illustrate the results.     

多个体切换网络分布式量化次梯度优化算法

由于已有的分布式次梯度算法大多基于理想的假设：网络拓扑是有向平衡的,构成网络的个体间通信的是各个个体某个状态变量的完全精确的信息。针对更一般的非平衡切换网络以及实际生活中网络通道的带宽限制,提出一种基于有限量化信息通信的切换网络分布式量化次梯度优化算法。在非平衡切换网络中,通过设计具有有限量化水平的一致量化器使所有信息在发送之前都经过量化,利用非二次李雅普诺夫函数方法,证明了所提出的多个体分布式量化次梯度优化算法的收敛性。最后仿真实例验证了所提算法的有效性,而且通过调节量化水平参数,在相同的带宽条件下,可提高信息传输速率,使网络中的个体更快地达到一致。该方法弱化了对刻画网络拓扑的邻接矩阵的假设及对网络带宽的要求,更具实用性。