This brief studies the finite-time distributed consensus problem of fractional-order multiagent systems (FOMASs) with disturbances over directed graphs (digraphs). By utilizing the finite-time Lyapunov stability theor...
详细信息
This brief studies the finite-time distributed consensus problem of fractional-order multiagent systems (FOMASs) with disturbances over directed graphs (digraphs). By utilizing the finite-time Lyapunov stability theorem and distributed estimator technique, a continuous estimator-based finite-time fully distributed algorithm with a fractional power is proposed. Under the designed algorithm, all agents' states globally converge to a common value within a finite time in a fully distributed manner. The upper bound of the finite time is given explicitly. Finally, a numerical example is provided to validate the results.
In this paper, a region-following formation control (RFFC) problem is studied for multi-agent systems. The objective of RFFC is to develop cooperative algorithms for agents to track the unknown center of dynamic regio...
详细信息
In this paper, a region-following formation control (RFFC) problem is studied for multi-agent systems. The objective of RFFC is to develop cooperative algorithms for agents to track the unknown center of dynamic region meanwhile maintaining a specified-configuration formation. Using the boundary layer approximation, a continuous RFFC algorithm is constructed to reduce the control chattering. During the movement, the formation can zoom or rotate subject to constraints of some environmental conditions. Finally, the effectiveness of the designed RFFC algorithm is shown by a numerical example.
In this paper, a distributed average tracking (DAT) problem is studied for Lipschitz-type of nonlinear dynamical systems. The objective is to design DAT algorithms for locally interactive agents to track the average o...
详细信息
In this paper, a distributed average tracking (DAT) problem is studied for Lipschitz-type of nonlinear dynamical systems. The objective is to design DAT algorithms for locally interactive agents to track the average of multiple reference signals. Here, in both dynamics of agents and reference signals, there is a nonlinear term satisfying a Lipschitz-type condition. Three types of DAT algorithms are designed. First, based on state-dependent-gain design principles, a robust DAT algorithm is developed for solving DAT problems without requiring the same initial condition. Second, by using a gain adaption scheme, an adaptive DAT algorithm is designed to remove the requirement that global information, such as the eigenvalue of the Laplacian and the Lipschitz constant, is known to all agents. Third, to reduce chattering and make the algorithms easier to implement, a couple of continuous DAT algorithms based on time-varying or time-invariant boundary layers are designed, respectively, as a continuous approximation of the aforementioned discontinuous DAT algorithms. Finally, some simulation examples are presented to verify the proposed DAT algorithms.
This paper studies the distributed average tracking problem for multiple time-varying signals generated by linear dynamics, whose reference inputs are nonzero and not available to any agent in the network. In the edge...
详细信息
This paper studies the distributed average tracking problem for multiple time-varying signals generated by linear dynamics, whose reference inputs are nonzero and not available to any agent in the network. In the edge-based framework, a pair of continuous algorithms with, respectively, static and adaptive coupling strengths is designed. Based on the boundary layer concept, the proposed continuous algorithm with static coupling strengths can asymptotically track the average of multiple reference signals without the chattering phenomenon. Furthermore, for the case of algorithms with adaptive coupling strengths, average tracking errors are uniformly ultimately bounded and exponentially converge to a small adjustable bounded set. Finally, a simulation example is presented to show the validity of theoretical results. (C) 2016 Elsevier Ltd. All rights reserved.
This paper studies the distributed average computation problem for multiple time-varying signals with bounded inputs. Based only on relative output measurements, a pair of continuous algorithms with, respectively, sta...
详细信息
This paper studies the distributed average computation problem for multiple time-varying signals with bounded inputs. Based only on relative output measurements, a pair of continuous algorithms with, respectively, static and adaptive coupling strengths are designed and utilized. From the concept of boundary layer approach, the proposed continuous algorithm with static coupling strengths can asymptotically obtain the average value of the multiple reference signals without chattering phenomenon. Furthermore, for the case of algorithms with adaptive coupling strengths, the calculation errors are uniformly ultimately bounded and exponentially converge to a small adjustable bounded set. Finally, a simulation example is presented to show the validity of the theoretical results. Copyright (c) 2015 John Wiley & Sons, Ltd.
By analyzing the living behaviors of eels, this paper proposes a new eel swarm intelligence algorithm. This paper first describes the behavior of migratory eels, extracts three important behaviors--density adaption, n...
详细信息
By analyzing the living behaviors of eels, this paper proposes a new eel swarm intelligence algorithm. This paper first describes the behavior of migratory eels, extracts three important behaviors--density adaption, neighboring learning and sex mutation, and establishes a model for the mathematical description of the three important behaviors. Based on rational organization of the three important behaviors, the eel algorithm is designed for continuous optimization problems. Finally, we test the performance of eel swarm intelligence algorithm via several selected benchmark problems. The results show that the algorithm, in terms of its excellent convergence speed and solving accuracy, is competitive tothe compared algorithms.
暂无评论