Synchronization of complex networks with coupling delays via adaptive pinning intermittent control

The problem of exponential synchronization for a class of general complex dynamical networks with nonlinear coupling delays by adaptive pinning periodically intermittent control is considered in this paper. We use the methods of the adaptive control, pinning control and periodically intermittent control. Based on the piecewise Lyapunov stability theory, some less conservative criteria are derived for the global exponential synchronization of the complex dynamical networks with coupling delays. And several corresponding adaptive pinning feedback synchronization controllers are designed. These controllers have strong robustness against the coupling strength and topological structure of the network. Using the delayed nonlinear system as the nodes of the networks, a numerical example of the complex dynamical networks with nonlinear coupling delays is given to demonstrate the effectiveness of the control strategy.     

Synchronization of Complex Dynamical Networks with Dynamical Behavior Links

In this paper, synchronization of a complex dynamical network (CDN) is investigated while the coupling connections of the network exhibit dynamic behavior. As it is shown in simulations, the dynamic links can cause synchronization losing in the network whereas the links in many real‐world CDNs have dynamic behavior. To analyzing the effect of these links, two different CDN models are considered: without time delays and with delays in the coupling connections. By means of Lyapunov(‐Krasovskii) theory, stability analysis of the error dynamics between the nodes of these CDNs and an introduced individual node is investigated which yields some conditions in the form of linear matrix inequalities (LMIs). These LMIs can be solved easily by various existing LMI solvers. Moreover, the gain matrices of state feedback controllers will be obtained by solving the LMIs. In the end, illustrative numerical examples are given to specify the effectiveness of the proposed method.     

Abstraction and control for Groups of robots

This paper addresses the general problem of controlling a large number of robots required to move as a group. We propose an abstraction based on the definition of a map from the configuration space Q of the robots to a lower dimensional manifold A, whose dimension is independent of the number of robots. In this paper, we focus on planar fully actuated robots. We require that the manifold A has a product structure A=G/spl times/S, where G is a Lie group, which captures the position and orientation of the ensemble in the chosen world coordinate frame, and S is a shape manifold, which is an intrinsic characterization of the team describing the "shape" as the area spanned by the robots. We design decoupled controllers for the group and shape variables. We derive controllers for individual robots that guarantee the desired behavior on A. These controllers can be realized by feedback that depends only on the current state of the robot and the state of the manifold A. This has the practical advantage of reducing the communication and sensing that is required and limiting the complexity of individual robot controllers, even for large numbers of robots.     

Robust impulsive synchronization of linear discrete dynamical networks

This paper,aims to study robust impulsive synchronization problem for uncertain linear discrete dynamical network. For the discrete dynamical networks with unknown but bounded linear coupling, by introducing the concept of uniformly positive definite matrix functions,some robust impulsive controllers are designed,which ensure that the state of a discrete dynamical network globally asymptotically synchronizes with an arbitrarily assigned state of an isolate node of the network. This paper also investigates the synchronization problem where the network coupling fianctions are uncertain but bounded nonlinear functions.Finally, two examples are simulated to illustrate our results.     

Synchronization of uncertain complex dynamical networks via adaptive control

In this paper, synchronization of an uncertain dynamical network with time‐varying delay is investigated by means of adaptive control schemes. Time delays and uncertainties exist universally in real‐world complex networks. Especially, parameters of nodes in these complex networks are usually partially or completely uncertain. Considering the networks with unknown or partially known nodes, we design adaptive controllers for the corresponding complex dynamical networks, respectively. Several criteria guaranteeing synchronization of such systems are established by employing the Lyapunov stability theorem. Analytical and numerical results show that the proposed controllers have high robustness against parameter variations including network topologies, coupling structures, and strength. Copyright © 2008 John Wiley & Sons, Ltd.     

Robust imp ulsive synchronization of linear discrete dynamical networks

This paper aims to study robust impulsive synchronization problem for uncertain linear discrete dynamical network. For the discrete dynamical networks with unknown but bounded linear coupling ,by introducing the concept of uniformly positive definite matrix functions ,some robust impulsive controllers are designed ,which ensure that the state of a discrete dynamical network globally asymptotically synchronizes with an arbitrarily assigned state of an isolate node of the network. This paper also investigates the synchronization problem where the network coupling functions are uncertain but bounded nonlinear functions.Finally ,two examples are simulated to illustrate our results.     

Global synchronization criteria of linearly coupled neural network systems with time-varying coupling.

In this paper, global synchronization of linearly coupled neural network (NN) systems with time-varying coupling is investigated. The dynamical behavior of the uncoupled system at each node is general, which can be chaotic or others; the coupling configuration is time varying, i.e., the coupling matrix is not a constant matrix. Based on Lyapunov function method and the specific property of Householder transform, some criteria for the global synchronization are obtained. By these criteria, one can verify whether the coupled system with time-varying coupling is globally synchronized, which is important and useful for both understanding and interpreting synchronization phenomena and designing coupling configuration. Finally, two simulations are given to demonstrate the effectiveness of the theoretical results.     

奇异Lur'e网络的自适应牵制聚类同步控制

本文分别研究了由奇异和非奇异Lur''e系统组成的具有多种耦合方式时滞复杂动态网络的聚类同步问题. 通过设计一类牵制反馈控制器, 仅控制当前聚类中与其它聚类有直接连接的Lur''e系统, 从而有效减少控制器个数同时降低控制成本. 考虑到网络具有多种耦合方式, 本文合理构造Lyapunov 泛函, 并有效利用扇形条件、非线性函数类概念、S过程以及Lyapunov 稳定性定理等方法, 分别给出奇异和非奇异Lur''e 动态网络实现聚类同步的判定条件. 此外, 为有效节省控制成本, 针对控制强度设计一类自适应更新定律, 从而得到网络实现聚类同步的最优控制强度. 最后, 为了验证所得聚类同步判定条件和控制器的有效性, 对一类典型Lur''e网络聚类同步问题进行了数值仿真.     

Closed-Curve Path Tracking for Decentralized Systems of Multiple Mobile Robots

In this paper we address the problem of making a group of mobile robots cooperatively track an assigned path. We consider paths described by completely arbitrarily shaped closed curves. The proposed control strategy is a fully decentralized algorithm and it does not require any global synchronization. The desired behavior is obtained by means of some properly designed artificial potential functions. Analytical proofs are provided to show the asymptotic convergence of the system to the desired behavior. Matlab simulations and experiments on real robots are described as well for validation purposes.     

Pinning adaptive synchronization of a general complex dynamical network

There are two challenging fundamental questions in pinning control of complex networks: (i) How many nodes should a network with fixed network structure and coupling strength be pinned to reach network synchronization? (ii) How much coupling strength should a network with fixed network structure and pinning nodes be applied to realize network synchronization? To fix these two questions, we propose a general complex dynamical network model and then further investigate its pinning adaptive synchronization. Based on this model, we attain several novel adaptive synchronization criteria which indeed give the positive answers to these two questions. That is, we provide a simply approximate formula for estimating the detailed number of pinning nodes and the magnitude of the coupling strength for a given general complex dynamical network. Here, the coupling-configuration matrix and the inner-coupling matrix are not necessarily symmetric. Moreover, our pinning adaptive controllers are rather simple compared with some traditional controllers. A Barabási-Albert network example is finally given to show the effectiveness of the proposed synchronization criteria.     

Event-triggered synchronization control for complex networks with uncertain inner coupling

This paper is concerned with the event-triggered synchronization control problem for a class of complex networks with uncertain inner couplings. The uncertain inner coupling under consideration is characterized in terms of the interval matrix. In order to save the communication and computation resources, the event-based mechanism is adopted and the event-triggered synchronization control scheme is proposed for the complex networks. First, we transform the event-triggered synchronization control problem into the exponential stabilization problem for a new class of dynamical systems with multiple delays. Then, by employing the Lyapunov stability theory, we derive a sufficient condition under which the multi-delayed system is exponentially stable. Subsequently, a set of event-triggered synchronization controllers is designed in terms of the solution to a linear matrix inequality that can be solved effectively by using available software. Finally, a numerical simulation example is presented to show the effectiveness of the proposed event-triggered control scheme.     

Evolving Self-Organizing Behaviors for a Swarm-Bot

In this paper, we introduce a self-assembling and self-organizing artifact, called a swarm-bot, composed of a swarm of s-bots, mobile robots with the ability to connect to and to disconnect from each other. We discuss the challenges involved in controlling a swarm-bot and address the problem of synthesizing controllers for the swarm-bot using artificial evolution. Specifically, we study aggregation and coordinated motion of the swarm-bot using a physics-based simulation of the system. Experiments, using a simplified simulation model of the s-bots, show that evolution can discover simple but effective controllers for both the aggregation and the coordinated motion of the swarm-bot. Analysis of the evolved controllers shows that they have properties of scalability, that is, they continue to be effective for larger group sizes, and of generality, that is, they produce similar behaviors for configurations different from those they were originally evolved for. The portability of the evolved controllers to real s-bots is tested using a detailed simulation model which has been validated against the real s-bots in a companion paper in this same special issue.     

Teamwork in Self-Organized Robot Colonies

Swarm robotics draws inspiration from decentralized self-organizing biological systems in general and from the collective behavior of social insects in particular. In social insect colonies, many tasks are performed by higher order group or team entities, whose task-solving capacities transcend those of the individual participants. In this paper, we investigate the emergence of such higher order entities. We report on an experimental study in which a team of physical robots performs a foraging task. The robots are “identical” in hardware and control. They make little use of memory and take actions purely on the basis of local information.      

一个新混沌系统的自适应模糊同步

本文基于Takagi-Sugeno(T-S)模糊模型,研究了混沌系统的自适应同步。基于T-S模糊模型重构了混沌系统,推导了在衰减率α下,自适应同步全局渐近稳定的充分条件;同时,在驱动系统参数未知的情况下,使用自适应参数调节律,得到响应系统参数的估计值。设计的模糊控制器均由线性函数构成,结构简单,规则少,有利于实际应用中构造控制器。数值仿真结果验证了方法的有效性。     

Symmetry and symmetry-breaking in multiagent behavior

This paper presents some results about properties of the spatial behavior of systems consisting of many artificial agents (robots). The general goal is to understand how the complexity of group behavior is related to individual behavior, and how differences arise and can be grounded. We argue that symmetry and symmetry-breaking are essential factors for the organization of spatial group behavior. They can serve as guiding principles for the construction of agents for real-world environments. This work was presented, in part, at the Second International Symposium on Artifical Life and Robotics, Oita, Japan, February 18–20, 1997     

An adaptive, self-organizing dynamical system for hierarchical control of bio-inspired locomotion

In this paper, dynamical systems made up of locally coupled nonlinear units are used to control the locomotion of bio-inspired robots and, in particular, a simulation of an insect-like hexapod robot. These controllers are inspired by the biological paradigm of central pattern generators and are responsible for generating a locomotion gait. A general structure, which is able to change the locomotion gait according to environmental conditions, is introduced. This structure is based on an adaptive system, implemented by motor maps, and is able to learn the correct locomotion gait on the basis of a reward function. The proposed control system is validated by a large number of simulations carried out in a dynamic environment for simulating legged robots.     

Robust Formation Control of Multiple Wheeled Mobile Robots

This paper considers formation control of a group of wheeled mobile robots with uncertainty. Decentralized cooperative robust controllers are proposed in two steps. In the first step, cooperative control laws are proposed for multiple kinematic systems with the aid of results from graph theory such that a group of robots comes into a desired formation. In the second step, cooperative robust control laws for multiple uncertain dynamic systems are proposed with the aid of backstepping techniques and the passivity properties of the dynamic systems such that multiple robots comes into a desired formation. Since communication delay is inevitable in cooperative control, its effect on the proposed controllers is analyzed. Simulation results show the effectiveness of the proposed controllers.     

Evolutionary robotics: the Sussex approach

We give an overview of evolutionary robotics research at Sussex over the last five years. We explain and justify our distinctive approaches to (artificial) evolution, and to the nature of robot control systems that are evolved. Results are presented from research with evolved controllers for autonomous mobile robots, simulated robots, co-evolved animats, real robots with software controllers, and a real robot with a controller directly evolved in hardware.     

复杂环境下群机器人自组织协同多目标围捕

针对动态多目标围捕,提出了一种复杂环境下协同自组织多目标围捕方法.首先设计了多目标在复杂环境下的运动模型,然后通过对生物群体围捕行为的研究,构建了多目标简化虚拟受力模型.基于此受力模型和提出的动态多目标自组织任务分配算法,提出了群机器人协同自组织动态多目标围捕算法,这两个算法只需多目标和个体两最近邻位置信息以及个体面向多目标中心方向的两最近邻任务信息,计算简单高效,易于实现.接着获得了系统稳定时参数的设置范围.由仿真可知,所提的方法具有较好的灵活性、可扩展性和鲁棒性.最后给出了所提方法相较于其它方法的优势.     

Adaptive synchronization of the complex dynamical network with double non-delayed and double delayed coupling

To simulate more realistic networks, we introduce a complex dynamical network model with double non-delayed and double delayed coupling and further investigate its synchronization phenomenon in this paper. Based on Lyapunov stability theory, adaptive synchronization criteria is obtained. Analytical result shows that under the designed adaptive controllers, the complex dynamical network with double non-delayed and double delayed coupling can asymptotically synchronize to a given trajectory. What is more, the coupling matrix is not assumed to be symmetric or irreducible. Finally, simulation results show the method is effective.