Flocking shape analysis of multi-agent systems

In this paper,we consider the shape control in flocking behavior of a multi-agent system with a virtual leader.Besides the traditional flocking control terms,which include a gradient-based term,a velocity consensus term and a navigational feed-back in general,a new piecewise smooth neighbor-based local controller is added to regulate the configuration to the desired flocking shape.All agent velocities approach the desired velocity asymptotically,while collisions among agents can be avoided.Furthermore,based...     

Flocking of multi‐agent dynamical systems with intermittent nonlinear velocity measurements

In this paper, the problem of flocking control in networks of multiple dynamical agents with intermittent nonlinear velocity measurements is studied. A new flocking algorithm is proposed to guarantee the states of the velocity variables of all the dynamical agents to converge to consensus while ensuring collision avoidance of the whole group, where each agent is assumed to obtain some nonlinear measurements of the relative velocity between itself and its neighbors only on a sequence of non‐overlapping time intervals. The results are then extended to the scenario of flocking with a nonlinearly dynamical virtual leader, where only a small fraction of agents are informed and each informed agent can obtain intermittent nonlinear measurements of the relative velocity between itself and the virtual leader. Theoretical analysis shows that the achieved flocking in systems with or without a virtual leader is robust against the time spans of the agent speed‐sensors. Finally, some numerical simulations are provided to illustrate the effectiveness of the new design. Copyright © 2011 John Wiley & Sons, Ltd.     

Flocking of multi-agent dynamical systems based on pseudo-leader mechanism

Flocking behavior of multiple agents can be widely observed in nature such as schooling fish and flocking birds. Recent literature has proposed the possibility that flocking can be achieved even with only a small fraction of informed agents with the desired position and velocity. However, it is still a challenging problem to determine which agents should be informed or have the ability to detect the desired information. This paper aims to address this problem. By combining the ideas of virtual force and pseudo-leader mechanism, where a pseudo-leader represents an informed agent who can detect the desired information, we propose a scheme for choosing pseudo-leaders in a multi-agent group, which can be applied to an unconnected or switching neighbor graph. Numerical examples are given to show the effectiveness of the methods presented in this paper.     

A connectivity-preserving flocking algorithm for multi-agent systems based only on position measurements

Most existing flocking algorithms rely on information about both relative position and relative velocity among neighbouring agents. In this article, we investigate the flocking problem with only position measurements. We propose a provably-stable flocking algorithm, in which an output vector is produced by distributed filters based on position information alone but not velocity information. Under the assumption that the initial interactive network is connected, the flocking algorithm not only can steer a group of agents to a stable flocking motion, but also can preserve the connectivity of the interactive network during the dynamical evolution. Moreover, we investigate the flocking algorithm with a virtual leader and show that all agents can asymptotically attain a desired velocity even if only one agent in the team has access to the information of the virtual leader. We finally show some numerical simulations to illustrate the theoretical results.     

邻域交互结构优化的多智能体快速蜂拥控制算法

针对多智能体系统在动态演化过程中容易出现的"局部聚集"现象,融 合复杂网络中的拓扑结构优化理论与多智能体系统协调蜂拥控制研究,提出了一种基 于邻域交互结构优化的多智能体快速蜂拥控制算法.该算法首先从宏观上分析多智 能体的局部聚集现象,利用社团划分算法将局部相对密集的多个智能体聚类成一个 社团,整个多智能体系统可以划分成多个相对稀疏的社团,并为每个社团选择度 最大的个体作为信息智能体,该个体可以获知虚拟领导者信息;随后从多智能体 系统中不同社团相邻个体间的局部交互结构入手,取消社团间相邻个体的交 互作用,设计仅依赖于社团内部邻居个体交互作用的蜂拥控制律;理论分 析表明,只要每个社团存在一个信息智能体,在虚拟领导者的引导作用下,整个多 智能体系统就可以实现收敛的蜂拥控制行为;仿真实验也证实了对多智 能体系统进行邻域交互结构优化可以有效提高整个系统的收敛速度.     

Flocking of Multi‐Agents Following a Leader with Adaptive Protocol in a Noisy Environment

This paper investigates the flocking problem of multi‐agents following a leader with communication delays in a noisy environment. Based on potential fields and the LaSalle‐type theorem for stochastic differential delay equations, by introducing the adaptive protocol compensating for the desired velocity, a new neighbor‐based flocking protocol is proposed such that all the agents move with a virtual leader's velocity almost surely, and avoidance of collision between the agents is ensured. A numerical example is given to illustrate the effectiveness of the proposed methods.     

Robust integral of sign of error-based distributed flocking control of double-integrator multi-agent systems with a varying virtual leader

This article investigates the flocking control problem of double-integrator multi-agent systems with a virtual leader subject to unknown external disturbances. A robust integral of sign of error (RISE) based control method is leveraged to design a distributed flocking controller with advantages of zero initial input value and continuous control input. By means of a new second-order differential virtual potential field function, and the navigational feedback from a virtual leader, the proposed flocking controller assures agents of velocity consensus with the virtual leader and a quasi -lattice formation within a circular neighborhood centered on the virtual leader. Moreover, this algorithm guarantees collision avoidance and connectivity preservation of a proximity-induced communication topology. Numerical simulations of the algorithm are provided to illustrate the effectiveness of the proposed flocking algorithm.     

Distributed adaptive flocking of robotic fish system with a leader of bounded unknown input

A distributed leader-follower flocking problem of multiple robotic fish governed by extended second-order unicycles is studied in this paper. The multi-agent system consists of only one leader with pre-appointed and bounded speeds. A distributed flocking algorithm on the basis of the combination of consensus and attractive/repulsive functions is investigated, in which adaptive strategy is adopted to compute the weight of the velocity coupling strengths. The proposed control algorithm enables followers to asymptotically track the leader’s varying velocities and approach the equilibrium distances with their neighbors. Furthermore, the arbitrarily-shaped formation flocking problem of the system can also be solved by adding the information of a desired formation topology to the potential function term. Finally, simulations are carried out to verify the effectiveness of the proposed theoretical results.     

Adaptive Flocking Control with a Minority of Informed Agents

In this paper, we address the flocking problem of multiple dynamic mobile agents with a virtual leader in a dynamic proximity network. To avoid fragmentation, we propose a novel flocking algorithm that consists of both an adaptive controller for followers and a feedback controller for the virtual leader. Based on our algorithm, all agents in the group can form a network, maintain connectivity, and track the virtual leader, even when only a minority of agents have access to the information of the virtual leader. Finally, several convincing simulation results are provided that demonstrate 2‐D flocking of a group of agents using the proposed algorithm.     

Flocking for multi-agent systems with optimally rigid topology based on information weighted Kalman consensus filter

This paper investigates the leader-follower flocking problem of multi-agent systems. The leader with input noise is estimated by a proposed continuous-time information weighted Kalman consensus filter (IWKCF) for agents. A novel distributed flocking algorithm based on the IWKCF is further presented to make agents achieve flocking to the leader. It is shown that the proposed flocking algorithm based on the continuous-time IWKCF is asymptotically stable. Applying the topology optimization scheme, the communication complexity of system topologies of multi-agent systems is effectively reduced. Finally, simulations are provided to demonstrate the effectiveness of the proposed results.     

A connection between formation infeasibility and velocity alignment in kinematic multi-agent systems

In this paper, a feedback control strategy that achieves convergence of a multi-agent system to a desired formation configuration is proposed for both the cases of agents with single integrator and nonholonomic unicycle-type kinematics. When inter-agent objectives that specify the desired formation cannot occur simultaneously in the state space the desired formation is infeasible. It is shown that under certain assumptions, formation infeasibility forces the agents’ velocity vectors to a common value at steady state. This provides a connection between formation infeasibility and flocking behavior for the multi-agent system. We finally also obtain an analytic expression of the common velocity vector in the case of formation infeasibility.     

Flocking of Multi-agent Systems with Unknown Nonlinear Dynamics and Heterogeneous Virtual Leader

This paper investigates the flocking control of multi-agent systems with unknown nonlinear dynamics while the virtual leader information is heterogeneous. The uncertain nonlinearity in the virtual leader information is considered, and the weaker constraint on the velocity information measurements is assumed. In addition, a bounded assumption on the unknown nonlinear dynamics is also considered. It is weaker than the Lipschitz condition adopted in the most flocking control methods. To avoid fragmentation, we construct a new potential function based on the penalty idea when the initial network is disconnected. A dynamical control law including a adjust parameter is designed to achieve the stable flocking. It is proven that the velocities of all agents approach to consensus and no collision happens between the mobile agents. Finally, several simulations verify the effectiveness of the new design, and indicate that the proposed method has high convergence and the broader applicability in practical applications with more stringent restrictions.

     

Flocking coordination using active leader and local information

In this paper coordination of a group of agents by a coordinator agent, called the leader‐agent (LA), is discussed. Agents have identical finite sensing radii and access only the local information. Inter‐agent interactions bring them together as a multi‐agent network system. In a recently proposed flocking algorithm using a virtual leader, it is proved that if a fraction of agents are informed then the center of mass of the multi‐agent system tracks the virtual leader. The minimum number of the fraction is always greater than one. In this paper the only informed agent is the LA. Interaction functions are defined to make the model of the multi‐agent system suitable for the design of the coordination control algorithm. The leader‐agent accesses its local data and actively plans its motions through a nonlinear control method. It is proven in this paper that the multi‐agent system tracks the virtual leader and a locally defined point near the LA converges to the position of the virtual leader. It is also shown that in this case, center of mass of the multi‐agent system follows the virtual leader but with a finite distance. We have also discussed positive effects of the LA on network connectivity. Finally illustrative examples are added as well. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Stable Flocking of Multiple Inertial Agents on Balanced Graphs

In this note, we consider the flocking of multiple agents which have significant inertias and evolve on a balanced information graph. Here, by flocking, we mean that all the agents move with a common velocity while keeping a certain desired internal group shape. We first show that flocking algorithms that neglect agents' inertial effect can cause unstable group behavior. To incorporate this inertial effect, we use the passive decomposition, which decomposes the closed-loop group dynamics into two decoupled systems: a shape system representing the internal group shape and a locked system describing the motion of the center-of-mass. Then, analyzing the locked and shape systems separately with the help of graph theory, we propose a provably stable flocking control law, which ensures that the internal group shape is exponentially stabilized to a desired one, while all the agents' velocities converge to the centroid velocity that is also shown to be time-invariant. This result still holds for slow-switching balanced information graphs. Simulation is performed to validate the theory.     

基于社区划分的多智能体网络快速蜂拥控制

针对复杂网络社区特性对多智能体系统协同控制效率的影响,面向具有ER(Erdos-renyi)网络或BA (Barabasi-albert)网络性质的多智能体系统,提出一种基于社区划分的快速蜂拥控制算法.该算法充分考虑社区内个体的相对密集特性,通过在社区间引入虚拟领导者作用,避免系统在演化过程中因通信受限而导致的“分块”现象,可有效提高系统拓扑的代数连通度.仿真结果表明:具有相应性质的多智能体系统蜂拥行为的收敛速度与ER和BA网络的平均度以及BA网络度分布的幂指数正相关;优化社区个数有利于提高蜂拥收敛速度.     

Fuzzy control of a class of autonomous formation constrained systems

This paper investigates the problem of controlling multiple mobile agents to maintain a desired geometric formation within a constrained environment. The influence of diversity of the perception radius and initial velocity is considered by using a fuzzy-logic-based potential function. A virtual leader is introduced to direct the group to track a desired path. Then the motion of the group is examined with the velocity damping and the mass of all the agents, respectively. By LaSalle’s invariant principle, not only the system stability can be guaranteed, but also the desired formation pattern without collisions with given boundary of a multi-agent system can be achieved. Numerical simulations are illustrated to demonstrate the effectiveness and robustness of the proposed control scheme.     

离散时变多智能体系统有限时间一致性迭代学习控制

针对一类离散时变多智能体系统,通过引入虚拟领导者产生期望轨迹的方法,将虚拟领导者和所有智能体组成固定的拓扑结构,在此基础上,提出一种离散时间迭代学习控制算法.该算法对多智能体系统中的每个智能体都设计一个控制器,各控制器都是利用上一次迭代时,该智能体与虚拟领导者之间的跟踪误差和该智能体与相邻智能体之间的跟踪误差,通过拓扑结构中通信权值的组合不断修正上一次的控制律,从而获得理想控制律.同时,基于范数理论严格证明所提出算法的收敛性,并给出算法在$\lambda$-范数意义下的收敛条件.该算法能够使离散时变多智能体的输出随着迭代次数的增加在有限时间区间内完全跟踪期望轨迹.理论分析和仿真结果都表明了所提出算法的有效性.     

Adaptive second-order consensus of networked mobile agents with nonlinear dynamics

We investigate second-order consensus of multiple nonlinear dynamical mobile agents with a virtual leader in a dynamic proximity network. We assume that only a small fraction of agents in the group have access to the information about the position and velocity of the virtual leader through, for example, certain pre-designed communication mechanism such as wireless broadcasting or sensing. To avoid fragmentation, we propose a connectivity-preserving second-order consensus algorithm. Under the assumption that the initial network is connected, we introduce local adaptation strategies for both the weights on the velocity navigational feedback and the velocity coupling strengths that enable all agents to synchronize with the virtual leader even when only one agent is informed, without requiring any knowledge of the agent dynamics. We finally provide some convincing simulation results to illustrate the theoretical results.     

Multiagent flocking with formation in a constrained environment

We consider the problem of controlling a group of mobile agents to form a designated formation while flocking within a constrained environment. We first propose a potential field based method to drive the agents to move in connection with their neighbors, and regulate their relative positions to achieve the specific formation. The communication topology is preserved during the motion. We then extend the method to flocking with environmental constraints. Stability properties are analyzed to guarantee that all agents eventually form the desired formation while flocking, and flock safely without collision with the environment boundary. We verify our algorithm through simulations on a group of agents performing maximum coverage flocking and traveling through an unknown constrained environment.     

Flocking of multi‐agent nonholonomic systems with unknown leader dynamics and relative measurements

In this paper, we consider the distributed flocking control problem of multi‐agent nonholonomic systems with a virtual leader whose dynamics is unknown; state information is time varying and not available to all agents under both fixed and switching topologies. On the basis of the relative velocity and orientation information of neighboring agents, two distributed discontinuous control protocols are designed for fixed and switching topologies, respectively. By using tools from algebraic graph theory and nonsmooth analysis, the proposed distributed discontinuous control protocols guarantee that the velocities and orientations of the agents exponentially converge to the velocity and orientation of the virtual leader, respectively, while ensuring collision avoidance of the whole group, if the interaction graph among agents is undirected and the virtual leader with bounded time‐varying velocity has directed paths to other agents. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2017 John Wiley & Sons, Ltd.