We study the mean-square composite-rotating consensus problem of second-order multi-agent systems with communication noises, where all agents rotate around a common center and the center of rotation spins around a fix...We study the mean-square composite-rotating consensus problem of second-order multi-agent systems with communication noises, where all agents rotate around a common center and the center of rotation spins around a fixed point simultaneously. Firstly, a time-varying consensus gain is introduced to attenuate to the effect of communication noises. Secondly, sufficient conditions are obtained for achieving the mean-square composite-rotating consensus. Finally, simulations are provided to demonstrate the effectiveness of the proposed algorithm.展开更多
Compared with the traditional consensus problem, this paper deals with the mean square average generalized consensus(MSAGC) of multi-agent systems under fixed directed topology, where all agents are affected by stocha...Compared with the traditional consensus problem, this paper deals with the mean square average generalized consensus(MSAGC) of multi-agent systems under fixed directed topology, where all agents are affected by stochastic disturbances. Distributed protocol depending on delayed time information from neighbors is designed. Based on Lyapunov stability theory, together with results from matrix theory and It o s derivation theory, the linear matrix inequalities approach is used to establish sufficient conditions to ensure MSAGC of multi-agent systems. Finally, numerical simulations are provided to illustrate the theoretical results.展开更多
In this paper, the mean square consensus control problem is investigated for linear uncertain discrete-time multi-agent systems withx-dependent noise and time-varying delays. Under undirected connected topology, the r...In this paper, the mean square consensus control problem is investigated for linear uncertain discrete-time multi-agent systems withx-dependent noise and time-varying delays. Under undirected connected topology, the robust consensus problem of multi-agent systems is converted into the robust stabilisation problem for thediscrete-time stochastic systems. By utilising Lyapunov functionaland the linear matrix inequality method, some new sufficient conditions are derived to guarantee the consensus of uncertain discretetime stochastic multi-agent systems. Based on the state feedbackcontroller protocol with time-varying delays, a new consensus criterion is established for the discrete-time stochastic multi-agent systems with parameter uncertainties. Finally, numerical examples areprovided to illustrate the effectiveness of the proposed results.展开更多
针对马尔可夫切换下离散和连续异质多智能体系统均方二分组一致问题,本文分别构造了2类包含合作竞争关系和马尔可夫切换拓扑结构异质多智能体系统均方二分组一致协议。利用随机不可约非周期矩阵(stochastic indecomposable and aperiodi...针对马尔可夫切换下离散和连续异质多智能体系统均方二分组一致问题,本文分别构造了2类包含合作竞争关系和马尔可夫切换拓扑结构异质多智能体系统均方二分组一致协议。利用随机不可约非周期矩阵(stochastic indecomposable and aperiodic matrices,SIA)相关性质、图论代数和矩阵分析等理论,得到相关系统实现均方二分组一致的充分必要条件。仿真实例说明了理论结果的有效性。展开更多
This paper considers the consensus problem of a group of homogeneous agents. These agents are governed by a general linear system and can only directly measure the output, instead of the state. In order to achieve the...This paper considers the consensus problem of a group of homogeneous agents. These agents are governed by a general linear system and can only directly measure the output, instead of the state. In order to achieve the consensus goal, each agent estimates its state through a Luenberger observer, exchanges its estimated state with neighbors, and constructs the control input with the estimated states of its own and neighbors. Due to the existence of observation and process noises, only practical consensus, instead of asymptotical consensus, can be achieved in such multi-agent systems. The performance of the achieved practical consensus can be measured by the ultimate mean square deviation of the states of agents. That performance is closely related to the observation gains of the state observers and the control gains of agents. This paper proposes a method to optimize such performance with respect to the concerned observation and control gains. That method starts with a set of feasible observation and control gains and formulates a group of linear matrix inequalities (LMIs). Solving these LMIs gives some intermediate matrix variables. By perturbing observation and control gains, and the intermediate matrix variables, the original LMIs yield another group of LMIs, which can be solved to provide a descent direction of observation and control gains. Moving along that descent direction, observation and control gains can be improved to yield better performance and work as the starting point of the next iteration. By iteratively repeating this procedure, we can hopefully improve the consensus performance of the concerned multi-agent system. Simulations are done to demonstrate the effectiveness of the proposed method.展开更多
This paper addresses the leader-following consensus problem of linear multi-agent systems(MASs) with communication noise. Each agent's dynamical behavior is described by a linear multi-input and multi-output(MIMO)...This paper addresses the leader-following consensus problem of linear multi-agent systems(MASs) with communication noise. Each agent's dynamical behavior is described by a linear multi-input and multi-output(MIMO) system, and the agent's full state is assumed to be unavailable. To deal with this challenge, a state observer is constructed to estimate the agent's full state. A dynamic output-feedback based protocol that is based on the estimated state is proposed. To mitigate the effect of communication noise, noise-attenuation gains are also introduced into the proposed protocol. In this study, each agent is allowed to have its own noise-attenuation gain. It is shown that the proposed protocol can solve the mean square leader-following consensus problem of a linear MIMO MAS. Moreover, if all noise-attenuation gains are of Q(t-β), where b∈(0,1), the convergence rate of the MAS can be quantitatively analyzed. It turns out that all followers' states converge to the leader's state in the mean square sense at a rate of O(t-β).展开更多
稀疏和随机动态变化是实际无线传感器网络(wireless sensor network,WSN)中普遍共同存在的两种通信拓扑不稳定因素,使基于一致性算法的分布式无迹信息滤波(distributed unscented information filter,DUIF)算法适用于稀疏动态WSN,将极...稀疏和随机动态变化是实际无线传感器网络(wireless sensor network,WSN)中普遍共同存在的两种通信拓扑不稳定因素,使基于一致性算法的分布式无迹信息滤波(distributed unscented information filter,DUIF)算法适用于稀疏动态WSN,将极大提高其实用性.为此,本文提出一种并行融合DUIF(parallel fusion DUIF,PF–DUIF)算法.在PF–DUIF算法中,通过将实时局部后验估计均值和协方差用于局部无迹信息滤波器(local unscented information filter,LUIF)的Sigma点采样,使LUIF和加权平均一致性滤波器(weighted average consensus filter,WACF)得以并行运行,从而有效抵制由通信拓扑随机动态变化带来的较大一致跟踪误差的困扰;同时,WACF通过对LUIF输出的无偏局部信息矩阵和向量分别进行平均一致性滤波,最终得到不包含由稀疏通信拓扑引起的平均一致误差的分布式后验估计结果;进而,建立即时更新机制有效抑制随机动态通信拓扑引起的PF–DUIF算法滤波异步问题,同时,基于稀疏动态WSN的平均网络模型,在通信能量消耗受限条件下优化WACF均方收敛速率,从而提高PF–DUIF算法的整体滤波效率.仿真实验结果表明,PF–DUIF算法能够有效应用于稀疏动态WSN机动目标跟踪.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61304155 and 11371049)Beijing Municipal Government Foundation for Talents,China(Grant No.2012D005003000005)
文摘We study the mean-square composite-rotating consensus problem of second-order multi-agent systems with communication noises, where all agents rotate around a common center and the center of rotation spins around a fixed point simultaneously. Firstly, a time-varying consensus gain is introduced to attenuate to the effect of communication noises. Secondly, sufficient conditions are obtained for achieving the mean-square composite-rotating consensus. Finally, simulations are provided to demonstrate the effectiveness of the proposed algorithm.
基金supported by the Natural Science Foundation of Jiangsu Province under Grant No.BK20161126the Prospective Research Project of Jiangsu Province under Grant No.BY2016022-17
文摘Compared with the traditional consensus problem, this paper deals with the mean square average generalized consensus(MSAGC) of multi-agent systems under fixed directed topology, where all agents are affected by stochastic disturbances. Distributed protocol depending on delayed time information from neighbors is designed. Based on Lyapunov stability theory, together with results from matrix theory and It o s derivation theory, the linear matrix inequalities approach is used to establish sufficient conditions to ensure MSAGC of multi-agent systems. Finally, numerical simulations are provided to illustrate the theoretical results.
基金This research is supported by the National Natural Science Foundation of China(Grant No.61573200,61573199).
文摘In this paper, the mean square consensus control problem is investigated for linear uncertain discrete-time multi-agent systems withx-dependent noise and time-varying delays. Under undirected connected topology, the robust consensus problem of multi-agent systems is converted into the robust stabilisation problem for thediscrete-time stochastic systems. By utilising Lyapunov functionaland the linear matrix inequality method, some new sufficient conditions are derived to guarantee the consensus of uncertain discretetime stochastic multi-agent systems. Based on the state feedbackcontroller protocol with time-varying delays, a new consensus criterion is established for the discrete-time stochastic multi-agent systems with parameter uncertainties. Finally, numerical examples areprovided to illustrate the effectiveness of the proposed results.
基金This work was supported by the National Natural Science Foundation of China (61273107, 61573077, 61503003), the Dalian Leading, Dalian, China, the Doctoral Foundation of Tianjin Normal University (135202XB1613), the Postdoctoral Science Foundation of China (2015M581332), and the Natural Science Foundation of Anhui Province (150808. 5QF126)
文摘针对马尔可夫切换下离散和连续异质多智能体系统均方二分组一致问题,本文分别构造了2类包含合作竞争关系和马尔可夫切换拓扑结构异质多智能体系统均方二分组一致协议。利用随机不可约非周期矩阵(stochastic indecomposable and aperiodic matrices,SIA)相关性质、图论代数和矩阵分析等理论,得到相关系统实现均方二分组一致的充分必要条件。仿真实例说明了理论结果的有效性。
基金The work of W. Zheng and Q. Ling was partially supported by the National Natural Science Foundation of China (No. 61273112) and the National Key Research and Development Project (No. 2016YFC0201003). The work of H. Lin was partially supported by the National Science Foundation (Nos. NSF-CNS-1239222, NSF-CNS-1446288, NSF-EECS-1253488).
文摘This paper considers the consensus problem of a group of homogeneous agents. These agents are governed by a general linear system and can only directly measure the output, instead of the state. In order to achieve the consensus goal, each agent estimates its state through a Luenberger observer, exchanges its estimated state with neighbors, and constructs the control input with the estimated states of its own and neighbors. Due to the existence of observation and process noises, only practical consensus, instead of asymptotical consensus, can be achieved in such multi-agent systems. The performance of the achieved practical consensus can be measured by the ultimate mean square deviation of the states of agents. That performance is closely related to the observation gains of the state observers and the control gains of agents. This paper proposes a method to optimize such performance with respect to the concerned observation and control gains. That method starts with a set of feasible observation and control gains and formulates a group of linear matrix inequalities (LMIs). Solving these LMIs gives some intermediate matrix variables. By perturbing observation and control gains, and the intermediate matrix variables, the original LMIs yield another group of LMIs, which can be solved to provide a descent direction of observation and control gains. Moving along that descent direction, observation and control gains can be improved to yield better performance and work as the starting point of the next iteration. By iteratively repeating this procedure, we can hopefully improve the consensus performance of the concerned multi-agent system. Simulations are done to demonstrate the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(Grant Nos.6142231061370032+2 种基金61225017&61421004)Beijing Nova Program(Grant No.Z121101002512066)Guangdong Provincial Natural Science Foundation(Grant No.2014A030313266)
文摘This paper addresses the leader-following consensus problem of linear multi-agent systems(MASs) with communication noise. Each agent's dynamical behavior is described by a linear multi-input and multi-output(MIMO) system, and the agent's full state is assumed to be unavailable. To deal with this challenge, a state observer is constructed to estimate the agent's full state. A dynamic output-feedback based protocol that is based on the estimated state is proposed. To mitigate the effect of communication noise, noise-attenuation gains are also introduced into the proposed protocol. In this study, each agent is allowed to have its own noise-attenuation gain. It is shown that the proposed protocol can solve the mean square leader-following consensus problem of a linear MIMO MAS. Moreover, if all noise-attenuation gains are of Q(t-β), where b∈(0,1), the convergence rate of the MAS can be quantitatively analyzed. It turns out that all followers' states converge to the leader's state in the mean square sense at a rate of O(t-β).
文摘稀疏和随机动态变化是实际无线传感器网络(wireless sensor network,WSN)中普遍共同存在的两种通信拓扑不稳定因素,使基于一致性算法的分布式无迹信息滤波(distributed unscented information filter,DUIF)算法适用于稀疏动态WSN,将极大提高其实用性.为此,本文提出一种并行融合DUIF(parallel fusion DUIF,PF–DUIF)算法.在PF–DUIF算法中,通过将实时局部后验估计均值和协方差用于局部无迹信息滤波器(local unscented information filter,LUIF)的Sigma点采样,使LUIF和加权平均一致性滤波器(weighted average consensus filter,WACF)得以并行运行,从而有效抵制由通信拓扑随机动态变化带来的较大一致跟踪误差的困扰;同时,WACF通过对LUIF输出的无偏局部信息矩阵和向量分别进行平均一致性滤波,最终得到不包含由稀疏通信拓扑引起的平均一致误差的分布式后验估计结果;进而,建立即时更新机制有效抑制随机动态通信拓扑引起的PF–DUIF算法滤波异步问题,同时,基于稀疏动态WSN的平均网络模型,在通信能量消耗受限条件下优化WACF均方收敛速率,从而提高PF–DUIF算法的整体滤波效率.仿真实验结果表明,PF–DUIF算法能够有效应用于稀疏动态WSN机动目标跟踪.