Coordination of Networked Nonlinear Multi-Agents Using a High-Order Fully Actuated Predictive Control Strategy

This paper is concerned with the coordinative control problem of networked nonlinear multi-agents (NNM) with communication delays. A high-order fully actuated (HOFA) model is introduced to describe the nonlinear multi-agents. Based on this model, a HOFA predictive coordination method is proposed to compensate for the communication delays actively and achieve simultaneous stability and consensus. This method largely simplifies the design of networked nonlinear multi-agents and makes the control performance be same for networked nonlinear multi-agents with and without communication delays. The analysis on the closed-loop systems derives the simultaneous stability and consensus criteria of networked nonlinear multi-agents using the HOFA predictive coordination method. With the presented way of designing HOFA predictive coordination controllers, a simulated example demonstrates the advantages of the proposed method.      

主动配电网中多代理模拟技术与应用研究

针对主动配电网(active distribution network,ADN)中分散式、主动性元件种类及数量的大幅增加,网络结构复杂管理控制难度日趋困难的问题,提出多代理技术是增加ADN中多类型主动性元件协调合作的新手段。该文综述了近年来国内外基于多代理系统对ADN中分布式能源管控、主动元件的协调控制、故障快速恢复以及区域自治的市场仿真4个方面的研究现状与成果,分析了多代理技术应用在ADN中的管理结构、通讯机制及适应于ADN发展的Agent模型。从ADN的主动性规划、多能流系统模式、博弈性市场机制及负荷主动管理能力等方面的发展趋势,展望了在未来如何更好地利用多代理技术,提高主动配电网的供电可靠性与经济性。     

A multi-agent architecture for dynamic scheduling of steel hot rolling

Steel production is a complex process and finding coherent and effective schedules for the wide variety of production steps, in a dynamic environment, is a challenging task. In this paper, we propose a multi-agent architecture for integrated dynamic scheduling of the hot strip mill (HSM) and the continuous caster. The scheduling systems of these processes have very different objectives and constraints, and operate in an environment where there is a substantial quantity of real-time information concerning production failures and customer requests. Each process is assigned to an agent which independently, seeks an optimal dynamic schedule at a local level taking into account local objectives, real-time information and information received from other agents. Each agent can react to real-time events in order to fix any problems that occur. We focus here, particularly, on the HSM agent which uses a tabu search heuristic to create good predictive–reactive schedules quickly. The other agents simulate the production of the coil orders and the real-time events, which occur during the scheduling process. When real-time events occur on the HSM, the HSM agent might decide whether to repair the current schedule or reschedule from scratch. To address this problem, a range of schedule repair and complete rescheduling strategies are investigated and their performance is assessed with respect to measures of utility, stability and robustness, using an experimental simulation framework.     

基于智能多代理的工作流资源分配

提出了一种基于智能多代理实现分布式工作流资源分配的方法。该方法采用KQML语言来设计资源分配代理和工作流引擎之间面向知识交换的通信协议,并且由Router提供消息存储和转发机制。工作流资源分配代理与工作流管理系统的其他代理程序通过KQML消息交流知识,从而达到在分布式、异构环境下的互操作。     

基于多代理系统的侦察机器人监控系统研制

针对半自主侦察机器人监控系统应该具有分布的智能、局部的自主能力和开放的系统构架的要求，建立了基于多代理机制的监控系统。系统主要分成感知代理、车体驱动代理、事务执行代理、操作员接口代理、数据管理代理等部分，这些代理又可以是由若干个代理协同工作的组合代理，代理之间采用控制驱动的协调方法。然后，分别介绍了感知代理、事务执行代理、人一机器人接口代理中主要代理的功能和实现方法。实验测试表明，系统满足侦察机器人的监控要求，具有很好的灵活性和扩展性。     

基于多Agent的机器人氧等离子切割系统

介绍了一种机器人氧等离子切割控制系统的设计方法.运用多智能体系统理论思想,从系统架构和系统控制两方面分析了系统原理,并着重研究了系统集成技术的工程实现.最后通过工程实例,将多Agent集成策略应用于机器人自动化系统,提高了系统的设计效率,降低了工程难度.     

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。     

基于多Agent的供应链系统的仿真研究

基于Agent的结构提供了一个通过网络进行的分布式工具和合作系统的途径.描述了多Agent系统的结构和使用工具.给出了供应链进行过程,介绍了供应链上的Agent实体的功能及其规则,并详细的描述了供应链上多Agent之间的交互过程.     

Neuro-adaptive cooperative tracking control with prescribed performance of unknown higher-order nonlinear multi-agent systems

This paper is concerned with the design of a distributed cooperative synchronisation controller for a class of higher-order nonlinear multi-agent systems. The objective is to achieve synchronisation and satisfy a predefined time-based performance. Dynamics of the agents (also called the nodes) are assumed to be unknown to the controller and are estimated using neural networks. The proposed robust neuro-adaptive controller drives different states of nodes systematically to synchronise with the state of the leader node within the constraints of the prescribed performance. The nodes are connected through a weighted directed graph with a time-invariant topology. Only few nodes have access to the leader. Lyapunov-based stability proofs demonstrate that the multi-agent system is uniformly ultimately bounded stable. Highly nonlinear heterogeneous networked systems with uncertain parameters and external disturbances were used to validate the robustness and performance of the new novel approach. Simulation results considered two different examples: single-input single-output and multi-input multi-output, which demonstrate the effectiveness of the proposed controller.     

Distributed robust finite-time nonlinear consensus protocols for multi-agent systems

This paper investigates the robust finite-time consensus problem of multi-agent systems in networks with undirected topology. Global nonlinear consensus protocols augmented with a variable structure are constructed with the aid of Lyapunov functions for each single-integrator agent dynamics in the presence of external disturbances. In particular, it is shown that the finite settling time of the proposed general framework for robust consensus design is upper bounded for any initial condition. This makes it possible for network consensus problems to design and estimate the convergence time offline for a multi-agent team with a given undirected information flow. Finally, simulation results are presented to demonstrate the performance and effectiveness of our finite-time protocols.