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In this paper, we are concerned with the team optimal decentralized state estimation problem where the state is transmitted to a remote agent with packet dropouts and is observed by N$$ N $$ local agents with additive noises. In particular, the information of the remote agent is available to all local agents with hierarchical relationships, which leads to an asymmetric information structure. The main contribution is to derive the analytical expressions for the team optimal decentralized state estimation. Different from the existing decentralized estimation results, the novelty of the paper is to comprehensively investigate the influence of packet dropouts and additive noises, which occur frequently in networked control systems. [ABSTRACT FROM AUTHOR]

In this paper, we study the cooperative output consensus problem of discrete-time heterogeneous multi-agent systems over nonidentical channel fading networks. Different from the traditional output consensus problem, the communication channels among agents are perturbed by stochastic multiplicative noises, which can also describe the packet loss phenomenon. The perturbed channels can result in a significant challenge for consensus analysis since their effect cannot be separated linearly from the communication topology. Based on the distributed feedforward control method, a novel distributed dynamic output feedback controller is developed to ensure output synchronization for each agent in the mean-square sense. To facilitate the consensus analysis, we utilize the relationship between the graph Laplacian matrix and the incidence matrix and matrix transformation technique, and find sufficient solvability conditions relying on each agent's dynamics, the maximum eigenvalue of communication graph and the packet loss probability for the scenarios of undirected graph and directed graph, respectively. Finally, simulation results are given to verify the theoretical analysis. [ABSTRACT FROM AUTHOR]

This study mainly concerns the linear quadratic optimal control and stabilisation problems for large‐scale systems with constraint, the constraint is imposed on the weighted control and state, which arises from coordination problem for multi‐agent systems. The main contributions of this study are: first, the optimal controller is developed via using the maximum principle and decoupling the forward and backward difference equations (FBDEs); secondly, by defining the Lyapunov function with the optimal cost function, the necessary and sufficient stabilisation conditions for the large‐scale systems are derived. The main techniques adopted in this study are the maximum principle and the solution to the FBDEs. It is noted that the optimal control strategy involves the centralised information of the weighted state average, but this can be easily accessed for the large‐scale‐system network. [ABSTRACT FROM AUTHOR]

In this paper, we consider a distributed convex optimization problem where the objective function is an average combination of individual objective function in multi‐agent systems. We propose a novel Newton Consensus method as a distributed algorithm to address the problem. This method utilises the efficient finite‐time average consensus method as an information fusion tool to construct the exact Newtonian global gradient direction. Under suitable assumptions, this strategy can be regarded as a distributed implementation of the classical standard Newton method and eventually has a quadratic convergence rate. The numerical simulation and comparison experiment show the superiority of the algorithm in convergence speed and performance. [ABSTRACT FROM AUTHOR]

Summary: This paper studies mean‐field games for multiagent systems with control‐dependent multiplicative noises. For the general systems with nonuniform agents, we obtain a set of decentralized strategies by solving an auxiliary limiting optimal control problem subject to consistent mean‐field approximations. The set of decentralized strategies is further shown to be an ε‐Nash equilibrium. For the integrator multiagent systems, we design a set of ε‐Nash strategies by exploiting the convexity property of the limiting problem. It is shown that under the mild conditions, all the agents achieve mean‐square consensus. [ABSTRACT FROM AUTHOR]

Abstract: This paper studies the consensus problem for a class of general third‐order multi‐agent systems on an undirected connected network. By employing a variables transformation, the consensus control problem can be turned into a asymptotical stability problem. Then we present a necessary and sufficient condition for guaranteeing consensus by using Routh‐Hurwitz stability criterion. And this result can be applied to a special case of third‐order integrator systems. Also we will present a tolerable communication time delay for third‐order integrator systems under the assumption that multi‐agent systems can reach consensus without communication delay. [ABSTRACT FROM AUTHOR]

This study deals with the problem of consensus error calculation for linear multi-agent systems (MASs) with system noises and measurement noises. It is supposed that there exist communication noises when the information exchanges among distinct agents. The agents cannot reach consensus due to the existence of the system noises. We aim to design proper distributed control protocol to calculate the consensus error for the MASs. The states of each agent and its neighbors are estimated by applying Kalman-filtering theory. The distributed control protocol is designed by employing the estimated state information. Then the consensus error is calculated via the unique solution of a Lyapunov equation. Finally, a simulation example is presented to verify the correctness of the proposed results. [ABSTRACT FROM AUTHOR]

This paper studies the consensusability of a continuous-time linear time-invariant multi-agent system (MAS) with time delay in an undirected network with N nodes. We show that the MAS can achieve consensus if and only if N -- 1 time-delay subsystems associated with the eigenvalues of the Laplacian matrix of the network are simultaneously asymptotically stable. By employing a linear matrix inequality (LMI) method, we present a controller design method for a MAS to reach consensus. We also obtain a bound on the maximum time delay for consensusability for a MAS with first-order integrator dynamics by using frequency-domain analysis. [ABSTRACT FROM AUTHOR]

In this paper, the design of the distributed suboptimal controller for discrete-time multi-agent systems is considered. The distributed controllers, which only use the state information of itself and the relative states of its neighbors, are designed based on the topological structure of the system. The suboptimal feedback gain matrices of the distributed controllers are presented by using the 'averaged' optimization approach. It is showed that the distributed suboptimal controller is existent and unique. The design method of the distributed controller is obtained by the iteration procedure step by step. An example is given as an illustration of the proposed results. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper studies the optimal distributed control design problem for both continuous-time and discrete-time systems. We consider an identical decoupled dynamical system and a coupled performance index which is described through the Laplacian matrix. It is showed that the optimal feedback gain matrix corresponds to a complete undirected graph for the Laplacian matrix in the cost function. We aim to get the distributed controllers that only use the information of its state and the states of its neighbors. The existence conditions of the optimal distributed control for special cost function are given and the asymptotic stability of the system is discussed. Examples are given to show the efficiency of the proposed results. [ABSTRACT FROM AUTHOR]

SUMMARY This paper studies the containment control problem for multi-agent systems consisting of multiple leaders and followers connected as a network. The objective is to design control protocols so that the leaders will converge to a certain desired formation while the followers converge to the convex hull of the leaders. A novel protocol is proposed by exploiting the control input information of neighbors. Both continuous-time and discrete-time systems are considered. For continuous-time systems, it is proved that the protocol is robust to any constant delays of the neighbors' control inputs. For discrete-time systems, a sufficient condition on the feedback gain for the containment control is given in terms of the time delay and graph information. Some numerical examples are given to demonstrate the results. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we are concerned with the consensus of multi-agent systems with input delay. Among all standard static protocols that achieve the consensus for the multi-agent system under no input delay, we aim to find the maximum input delay such that the system remains consensusable under the same protocols. In the case of continuous-time systems, in view of the continuity of stability with respect to the time delay, the maximum delay margin for consensusability is given for scalar systems and vector systems with a single unstable open-loop pole. For scalar discrete-time systems, we show that the maximum delay margin for consensusability is strictly greater than zero if and only if the open-loop pole of the system is located in a specified interval. [Copyright &y& Elsevier]

This paper considers bounded consensus problem of continuous-time linear multi-agent systems with both additive system and communication noises under an undirected communication topology. Owning to the coexistence of the additive system and communication noises, the exact consensus cannot reach. Hence, the distributed controller is to be designed such that all the agents can reach to a collection behavior to some degree. It is supposed that each agent can obtain full state of itself and receive its neighbors' state with additive noises. For each agent, the consensus protocol is designed based on the error between the estimated state of its neighbors' and full state of itself. By means of Kalman filtering and matrix analysis, the bound of consensus is given via the solution of a Lyapunov equation. Finally, a simulation example is presented to demonstrate the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper is concerned with the consensus control problem for multi-agent systems with agents characterized by high-order linear continuous-time systems subject to communication delays between neighbouring nodes in the network. A new consensus protocol is proposed. It requires communication between neighbouring agents only at certain sampling points, rather than at all times. It is also unique in the sense that it is nonlinear in the continuous-time domain but linear when the agents are viewed in the sampled-data domain. Under the proposed consensus protocol, marginally stable multi-agent systems can reach consensus for any large delay. Unstable multi-agent systems achieve consensus when the time delay is within a certain range. Moreover, in the single-input case, we give an optimal control gain which yields the fastest consensus speed. The proposed technique is expected to pave a new way for new theoretical studies on network properties required for consensus control. [ABSTRACT FROM AUTHOR]

This paper studies the consensus problem for a class of general second-order multi-agent systems (MASs) with communication delay. We first consider the delay-free case and obtain a necessary and sufficient condition for consensus. Then, based on the obtained conditions for the delay-free case, we deduce an explicit formula for the delay margin of the consensus for the case with time delay using the relationship between the roots of the characteristic equation and the time delay parameter. In addition, we consider the special case where the second-order model is a double integrator. For this case, simpler consensus conditions under communication delay are provided. [ABSTRACT FROM AUTHOR]

Abstract: This paper studies the consensusability problem of continuous-time multi-agent systems with time-varying communication delay in undirected network. We design a consensus protocol based on the low gain solution of a parametric algebraic Riccati equation (ARE) and not use the precise information of the amount of time-varying delay. By studying the joint effect of agent dynamic and network topology, sufficient conditions are given for consensus when all poles of the system matrix are on the closed left-half plane. In case of non-zero poles on the imaginary axis, maximal admissible upper bound of the time-varying delay is given in terms of both the agent dynamic and network topology; otherwise, consensus can be achieved for the time-varying delay with arbitrarily large upper bound. Finally, simulation results are presented to demonstrate the effectiveness of the theoretical results. [Copyright &y& Elsevier]

Abstract: This paper studies the distributed consensus problem for linear discrete-time multi-agent systems with delays and noises in transmission channels. Due to the presence of noises and delays, existing techniques such as the lifting technique and the stochastic Lyapunov theory are no longer applicable to the analysis of consensus. In this paper, a novel technique is introduced to overcome the difficulties induced by the delays and noises. A consensus protocol with decaying gains satisfying persistence condition is adopted. Necessary and sufficient conditions for strong consensus and mean square consensus are respectively given for non-leader–follower and leader–follower cases under a fixed topology. Under dynamically switching topologies and randomly switching topologies, sufficient conditions for strong consensus and mean square consensus are also obtained. Numerical examples are given to demonstrate the effectiveness of the proposed protocols. [Copyright &y& Elsevier]

This paper studies a distributed state estimation problem for a network of linear dynamic systems (called nodes), which evolve autonomously, but their measurements are coupled through neighborhood interactions. Power networks are typical networked systems obeying such features, with other examples including traffic networks, sensor networks and many multi-agent systems. We develop a new distributed state estimation approach, for each node to update its local state. The core of this distributed approach is a distributed maximum a posteriori (MAP) estimation technique, which delivers a globally optimal estimate under certain assumptions. We apply the distributed approach to an IEEE 118-bus system, and compare it with a centralized approach, which provides the optimal state estimate using all the measurements, and with a local state estimation approach, which uses only local measurements to estimate local states. Simulation results show that under different scenarios including normal operation, bad measurements and sudden load change, the distributed approach is clearly more accurate than the local state estimation approach and distributed static state estimation approach. Although the result is a bit less accurate than that by a centralized algorithm, the distributed algorithm enjoys low computational complexity and communication load, and is scalable to large power networks. [ABSTRACT FROM AUTHOR]