基于位置信息的混合多智能体蜂拥控制方法

目前,很多蜂拥控制算法都是基于智能体通信半径为一个固定的值且既考虑多智能体之间的相对位置,又考虑它们的相对速度来设计的,然而,实际的情况往往不会有那么理想。文中试图在基于通信半径不同的混合多智能体控制策略的设计过程中减少考虑的控制因素的个数（只考虑位置信息）,提出一种分布式的控制算法。此控制算法能实现多智能体跟随一个速度固定的虚拟领航者,形成聚合、无碰撞的队列。给出了算法的可行性理论分析,并针对20个智能体跟踪一个速度固定的虚拟领导者的情形给出了计算机仿真,用以验证算法的可行性。     

基于事件触发二阶多智能体系统的固定时间比例一致性

研究了在无向拓扑下,由多个子群组成的二阶多智能体系统的固定时间比例一致性问题,采用反推法设计了一种基于事件触发的固定时间非线性比例一致控制策略,该策略包含分段式事件触发函数:当智能体在追踪虚拟速度时,给出了基于速度信息的触发条件;当智能体速度与虚拟速度达到一致时,切换至基于位置信息的触发条件,可有效减少系统能量耗散及控...     

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.     

二阶多智能体系统量化蜂拥控制

针对在多智能体系统的通信网络中需要对交换信息进行量化的客观情况,研究基于量化信息的二阶多智能体系统蜂拥控制问题。首先,假设多智能体系统采用一致量化器对速度和位置信息进行量化,并且有一个虚拟领导者沿着固定方向匀速运动;然后,设计基于量化信息的多智能体蜂拥控制输入,并利用非平滑系统的Lyapunov稳定性判据和不变集原理证明系统的稳定性;最后,利用Matlab对多智能体系统在二维平面上的蜂拥运动进行仿真实验,仿真结果验证了理论分析的正确性。     

具有时变通信延迟的多智能体系统改进蜂拥控制

针对不确定非线性二阶多智能体系统中存在的时变通信时延和未知干扰问题,提出了一种鲁棒自适应蜂拥控制规律。为了使二阶多智能体系统能够具有更好的抗干扰能力,设计了基于智能体位置状态信息和速度状态信息的鲁棒自适应算子,实现了系统在时变通信时延扰动下的分布控制。通过使用Lyapunov-Krasovskii方法构造能量函数,证明了多智能体系统的网络连通性,智能体的速度收敛于虚拟领导者的速度,并给出了具有时变通信时延的多智能体系统收敛条件。仿真实验结果表明,在不同干扰强度和不同通信时延下系统均能实现快速收敛,形成稳定的拓扑结构,证明所提方法正确有效。     

非仿射非线性多智能体系统迭代学习一致跟踪

为了解决非仿射非线性多智能体系统在给定时间区间上一致性完全跟踪问题,基于迭代学习控制方法设计一种分布式一致性跟踪控制算法.首先,由引入的虚拟领导者与所有跟随者组成多智能体系统的通信拓扑,其中虚拟领导者的作用是提供期望轨迹.然后,在只有部分跟随者能够获得领导者信息的条件下,利用每个跟随者及其邻居的跟踪误差构造每个跟随者的迭代学习一致性跟踪控制器.同时采用中值定理将非仿射非线性多智能体系统转化仿射形式,并基于压缩映射方法证明所提算法的收敛性,给出算法的收敛条件.理论分析表明,在智能体的非线性函数未知情况下,利用所提算法可以使非仿射非线性多智能体系统在给定时间区间上随迭代次数增加逐次实现一致性完全跟踪.最后,通过仿真算例进一步验证所提算法的有效性.     

数据丢失下多智能体系统迭代学习跟踪控制

考虑数据丢失下非线性多智能体系统的一致性跟踪问题。假设多智能体系统使用固定网络通信拓扑结构,由于通信网络自身限制导致多智能体系统中存在数据丢失现象。将数据丢失现象描述为取值0/1的随机伯努利序列,设计分布式一致性跟踪误差,提出该系统在数据丢失下的P型迭代学习控制算法。采用压缩映射的方法给出收敛性条件,并在理论上分析了跟踪误差的收敛性。仿真结果表明,提出的算法可以实现该系统在有限时间区间上对期望轨迹的完全跟踪,验证了算法的有效性。     

Round-Robin协议下基于观测器的多智能体系统H∞一致性控制

针对一类具有非线性动态特性的多智能体系统,研究Round-Robin(RR)通信协议下基于观测器的H_∞一致性控制问题。在智能体与其邻居智能体之间的通信信道引入了Round-Robin通信协议,缓解信道拥堵带来的测量丢失、时延等问题。通过RR协议的调度,使得智能体在每一时刻确保能够接收到一个邻居智能体信息。首先,根据智能体的测量输出设计状态观测器,对每个智能体的状态进行估计,然后,根据估计状态设计一致性控制器,基于李雅普诺夫稳定性理论,给出多智能体系统满足H_∞一致性性能指标的充分条件,进而通过求解线性矩阵不等式(LMI)获得观测器及控制器参数。最后,将本文设计的控制算法应用于数值仿真和柔性连杆机器人的一致性控制,验证所设计算法的可行性和有效性。     

输出饱和多智能体系统的迭代学习趋同跟踪控制

针对带有输出饱和的多智能体系统有限时间趋同跟踪控制问题,提出了一种分布式迭代学习控制算法.首先假设多智能体系统具有固定拓扑结构,且仅有部分智能体可获取到期望轨迹信息.基于输出约束条件构造一致性跟踪误差,在此基础上设计了P型迭代学习控制率.然后采用压缩映射方法给出了一个算法收敛的充分条件,并在理论上证明了跟踪误差的收敛性.最后,将理论结果推广至具有随机切换拓扑结构的多智能体系统中.仿真结果验证了所提出算法的有效性.     

利用方位角信息的移动机器人编队控制

本文以移动机器人为研究对象,仅利用方位角信息实现多智能体系统的编队控制.为实现大规模编队和队形的缩放控制,智能体被分为领航者、第1跟随者以及其余跟随者.首先,考虑智能体之间相对位置信息难以精确测量的情形,设计仅用方位角信息的估计算法获得准确的相对位置;然后,基于获得的相对位置信息设计第1跟随者的控制算法,使得第一跟随者...     

Nonlinear formation control strategies for agents without relative measurements under heterogeneous networks

This paper proposes cooperative control protocols for a group of unmanned vehicles to make a stable formation around a maneuvering target. The control protocols are proposed on the basis of heterogeneous communication networks, which represents more challenging and generalized situations. Two different scenarios are considered. Separate control protocols are developed for each case. In both scenarios, agents do not have relative position, velocity, and acceleration measurements as feedback. In the first scenario, each agent uses its own position and velocity measurement in a consensus algorithm. In the second scenario, each agent needs only its own position information for the consensus algorithm. For both protocols, agents compute virtual estimates of a target's position and velocity and exchange these among the neighbors. Three different communication networks are used for exchanging two virtual estimates calculated by each agent and a time derivative of one virtual estimate. Each interagent communication network is represented by a fixed, undirected, and connected graph. Furthermore, it is considered that at least one agent receives the position, velocity, and acceleration information of the maneuvering target. It is not necessary that the agent receiving the target's position and the agent receiving the velocity and/or the acceleration information of the target be the same. However, the target does not receive any information about any agent. Stability of the formation is analyzed by using Barbalat's lemma. It is also shown that, despite the large difference in received information, the acceleration of the agents remains bounded for all time. The performance of the proposed formation control protocols is illustrated through numerical simulations.     

Finite-time formation of multiple agents based on multiple virtual leaders

The finite-time formation problem of multiple agents aims to find a control protocol to guarantee finite-time consensus, in which every agent can be in the right position and keep in the given formation configuration efficiently. However, it is hard to achieve a stable state if only by setting one virtual leader in multiple tasks system. This paper presents a formation controller design for a second-order multiple agents to address the finite-time formation problem. In the procedure, each agent has a virtual leader, and then a control law is designed so that the agents can keep pace with their virtual leaders in terms of speed and position. Accordingly, the controller can ensure that the relative positions among different agents and the trajectory of the whole formation can be specified in advance. Moreover, since the closed-loop system is finite-time stable, which implies that the required formation is attainable without a deviation in finite time. Finally, the stability analysis is proved by applying the graph theory, Lyapunov stability theory and homogeneous system theory. The effectiveness of the algorithm is demonstrated by numerical simulations.     

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.     

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.     

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.     

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.     

Distributed adaptive output feedback tracking control for a class of uncertain nonlinear multi-agent systems

This paper addresses the distributed output feedback tracking control problem for multi-agent systems with higher order nonlinear non-strict-feedback dynamics and directed communication graphs. The existing works usually design a distributed consensus controller using all the states of each agent, which are often immeasurable, especially in nonlinear systems. In this paper, based only on the relative output between itself and its neighbours, a distributed adaptive consensus control law is proposed for each agent using the backstepping technique and approximation technique of Fourier series (FS) to solve the output feedback tracking control problem of multi-agent systems. The FS structure is taken not only for tracking the unknown nonlinear dynamics but also the unknown derivatives of virtual controllers in the controller design procedure, which can therefore prevent virtual controllers from containing uncertain terms. The projection algorithm is applied to ensure that the estimated parameters remain in some known bounded sets. Lyapunov stability analysis shows that the proposed control law can guarantee that the output of each agent synchronises to the leader with bounded residual errors and that all the signals in the closed-loop system are uniformly ultimately bounded. Simulation results have verified the performance and feasibility of the proposed distributed adaptive control strategy.     

Receding horizon tracking control of unicycle‐type robots based on virtual structure

This paper considers the receding horizon tracking control of the unicycle‐type robot subject to coupled input constraint based on virtual structure. The tracking position of the follower is considered to be a virtual structure point with respect to a Frenet–Serret frame fixed on the leader, and the desired control input of the follower not only depend on the input of the leader but also the separation vector. Firstly, a sufficient input condition for the leader robot is given to enable the follower to track its desired position while satisfying its inputs constraint. Secondly, receding horizon control scheme is designed for the follower robot, in which the recursive feasibility is guaranteed by developing a diamond‐shaped positively invariant terminal‐state region and its corresponding controller. Finally, simulation results are provided to verify the effectiveness of the scheme proposed. Copyright © 2016 John Wiley & Sons, Ltd.