Improvement Mechanism of Adhesion Performance of Anti-stripping Agents and Coupling Agents on Asphalt-Aggregate Interface Based on Molecular Dynamics

This study examined the mechanisms for improving the adhesion performance of the asphalt-aggregate interface with two anti-stripping agents and two coupling agents.The investigation of contact behavior between various asphalt-aggregate surfaces was conducted using molecular dynamics(MD)simulations.The interaction energy and the relative concentration distribution were employed as the parameters to analyze the enhancement mechanisms of anti-stripping agents and coupling agents on the asphalt-aggregate interface.Results indicated that the adhesion at the asphalt-aggregate interface could be strengthened by both anti-stripping agents and coupling agents.Anti-stripping agents primarily improve adhesion through the reinforcement of electrostatic attraction,while coupling agents primarily upgrade adhesion by strengthening the van der Waals.Hence,the molecular dynamics modeling and calculation techniques presented in this study can be utilized to elucidate the development mechanism of the asphalt-aggregate interface through the use of anti-stripping agents and coupling agents.

Distributed Consensus of High-Order Multi-Agents with Nonlinear Dynamics

This paper deals with the distributed consensus problem of high-order multi-agent systems with nonlinear dynamics subject to external disturbances. The network topology is assumed to be a fixed undirected graph. Some sufficient conditions are derived, under which the consensus can be achieved with a prescribed norm bound. It is shown that the parameter matrix in the consensus algorithm can be designed by solving two linear matrix inequalities (LMIs). In particular, if the nonzero eigenvalues of the laplacian matrix ac-cording to the network topology are identical, the parameter matrix in the consensus algorithm can be de-signed by solving one LMI. A numerical example is given to illustrate the proposed results.

Integrated Control of Lateral and Vertical Vehicle Dynamics Based on Multi-agent System

The existing research of the integrated chassis control mainly focuses on the different evaluation indexes and control strategy. Among the different evaluation indexes, the comprehensive properties are usually not considered based on the non-linear superposition principle. But, the control strategy has some shortages on tyre model with side-slip angle, road adhesion coefficient, vertical load and velocity. In this paper, based on belief, desire and intention（BDI）-agent model framework, the TYRE agent, electric power steering（EPS） agent and active suspension system（ASS） agent are proposed. In the system（SYS） agent, the coordination mechanism is employed to manage interdependences and conflicts among other agents, so as to improve the flexibility, adaptability, and robustness of the global control system. Due to the existence of the simulation demand of dynamic performance, the vehicle multi-body dynamics model is established by SIMPACK. And then the co-simulation analysis is conducted to evaluate the proposed multi-agent system（MAS） controller. The simulation results demonstrate that the MAS has good effect on the performance of EPS and ASS. Meantime, the better road feeling for the driver is provided considering the multiple and complex driving traffic. Finally, the MAS rapid control prototyping is built to conduct the real vehicle test. The test results are consistent to the simulation results, which verifies the correctness of simulation. The proposed research ensures the driving safety, enhances the handling stability, and improves the ride comfort.

基于多Agent的柔性作业车间动态调度方法研究

为提高调度策略对工件到达密度变化的适应能力,对柔性作业车间内的动态调度方法进行了研究。首先根据调研结果以及Agent建模方法构建了基于多Agent系统的柔性制造动态调度系统;然后结合柔性制造背景下的复杂结构件加工特点对调度过程中任务分解、机床选择、任务分配3个步骤的运行机制进行了改进,形成了基于工序块的任务分解机制、基于加工精度的机床选择机制以及基于调度规则的动态时间窗调度方法;最后通过试验验证了该动态调度方法在工件到达密度变化场景下的可行性,对当前实际的柔性作业车间生产活动具有一定的指导意义。

Self-triggered Consensus Control for Linear Multi-agent Systems With Input Saturation

In this paper, we study the consensus problem for a class of linear multi-agent systems(MASs) with consideration of input saturation under the self-triggered mechanism. In the context of discrete-time systems, a self-triggered strategy is developed to determine the time interval between the adjacent triggers. The triggering condition is designed by using the current sampled consensus error. Furthermore, the consensus control protocol is designed by means of a state feedback approach. It is shown that the considered multi-agent systems can reach consensus with the presented algorithm. Some sufficient conditions are proposed in the form of linear matrix inequalities(LMIs) to show the positively invariant property of the domain of attraction(DOA). Moreover, some sufficient conditions of controller synthesis are provided to enlarge the volume of the DOA and obtain the control gain matrix. A numerical example is simulated to demonstrate the effectiveness of the theoretical analysis results.

CONSENSUS ANALYSIS AND DESIGN OF LINEAR INTERCONNECTED MULTI-AGENT SYSTEMS

We deal with the state consensus problem of a general Linear Interconnected Multi-Agent System （LIMAS） under a time-invariant and directed communication topology. Firstly, we propose a linear consensus protocol in a general form, which consists of state feedback of the agent itself and feedback form of the relative states between the agent and its neighbors. Secondly, a state-linear-transformation is applied to equivalently transform the state consensus problem into a partial stability problem. Based on the partial stability theory, we derive a sufficient and necessary criterion of consensus convergence, which is expressed via the Hurwitz stability of a real matrix constructed from the parameters of the agent models and the protocols, and present an analytical formula of the consensus function. Lastly, we propose a design procedure of the gain matrices in the protocol by solving a bilinear matrix inequality.

Leaderless and leader-following consensus of linear multi-agent systems

This paper studies the consensus problems for multi-agent systems with general linear and nonlinear dynamics. The leaderless and leader-following consensus problems are investigated respectively. Contraction theory is employed to gen- erate some sufficient conditions for testing the agents reaching consensus. Under these conditions and certain assumptions, the trajectories of multi-agent systems in directed topology will converge to each other. Finally, two numerical examples are given to illustrate the effectiveness of the proposed results,

Dynamic Target Enclosing Control Scheme for Multi-Agent Systems via a Signed Graph-Based Approach

Dear Editor,This letter investigates the target enclosing control problem of multi-agent systems.A signed graph-based control strategy is presented,where the agents are steered to enclose the dynamic target from both sides as they move.This is inspired by the phenomenon that signed networks exhibit bipartite clustering if the underlying graph is structurally balanced,so that the agents may naturally enclose the zero point from opposite sides(+and.)if proper controllers are applied.By adopting a distributed observer to estimate the information of dynamic target。

基于免疫多Agent技术的煤矿综合能耗B/S动态监控方法

为实现煤矿内所有耗能设备的动态监控,为节能优化措施的提出提供重要依据,进一步贯彻落实国家绿色低碳环保的发展理念,提出基于免疫多Agent技术的煤矿综合能耗B/S动态监控方法。结合自动控制理论和计算机技术,根据分站控制原理,合理划分煤矿内能源消耗设备的类型,并为每个设备配备可编程控制器。通过极大似然估计法构建线性方程,确定各组设备的监测节点位置。利用多种通信协议,在三层网络结构中部署B/S监测架构,从计量终端收集煤矿能耗设备的运行数据。基于免疫多Agent技术构建学习模型,分析并推理接收到的数据信息,实现对煤矿综合能耗的动态监测。结果表明:以不同的能耗设备为测试对象,基于免疫多Agent技术的煤矿综合能耗B/S动态监控方法可以准确地获取全部运行信息,有效实现能耗设备的动态监测,能够全面监控煤矿中所有耗能设备的运行情况,并为其后期运行和管理提供理论依据,具有应用价值。

移动边缘计算下移动Agent的任务安全迁移策略

移动边缘计算中任务多在远离服务中心的边缘节点上执行,边缘节点的安全能力并不能得到保障,如何将任务迁移到安全可靠的边缘节点来执行是当前存在的一个问题。针对移动边缘计算下任务迁移中的安全风险问题,构建了适用于移动边缘计算环境的移动Agent安全风险计算模型,通过风险采集、风险处理和风险反馈综合评估边缘节点的抗风险值;并引入动态免疫算法,在任务计算和安全计算时间满足任务截止时间的前提下,实现任务迁移的安全能力最大化。仿真实验表明,相比于传统的任务迁移方案,该策略大大提高了移动边缘计算中任务迁移的抗风险能力,具有一定的鲁棒性。

Linear-contract Mechanisms Based on the Risk Preference of an Agent in a Supply Chain

With respect to different risk preference of an agent in a supply chain, linear-contract models are designed according to the principal-agent theory. The study shows that the risk preference of an agent directly correlates with the incentive compensation coefficient of principal, order quantity of principal and production capability level of the agent. The principal should offer an appropriate incentive contract according to the risk preference of the agent, or choose an agent holding a different risk preference to establish the supply chain.

多Agent动态影响图及其一种近似推理算法研究

针对多Agent影响图不能建模动态环境和多Agent马尔可夫决策过程难以表示Agents之间结构关系的问题,提出一种新决策模型——多Agent动态影响图(MADIDs).为了能有效地对MADIDs进行推理,提出一种扩展的BK(EBK)近似推理算法,其扩展体现在三个方面:在BK算法中加入效用结点的边际化操作,加入分割团来减小BK算法的推理误差,使用MADIDs分层分解所生成的联合树来降低推理的复杂性.在模型实例上的实验结果显示了MADIDs模型和EBK算法的有效性.

基于Multi-agent的分布式系统负载平衡

为实现分布式系统的动态负载平衡 ,基于Multi agent提出了一种新的分布式系统动态负载平衡算法 .该算法采用接收者启动的策略 ,根据各主机的负载状态 ,在系统运行过程中利用移动Agent动态迁移任务 .文中研究了主机负载状态 ,提出了负载状态指标 :〈LC,LM〉 ,该指标反映了分布式测控系统中各主机的异构性特点 .文中还详细介绍了Agent的功能、结构及通信 ,并且通过实例对Agent通信及如何创建移动Agent进行了说明 .将所提算法应用于分布式测控系统 ,结果表明 ,该算法能有效地减少网络传输、节省时间、提高系统效率和实现动态负载均衡 .

自适应多Agent系统的运行机制和策略描述语言SADL

自适应系统具有环境开放性、变化敏感性、系统动态性等复杂性特点,如何支持这类复杂系统的开发和维护是目前软件工程关注的焦点.将自适应系统中的自主运行单元抽象为软件Agent,借助组织学思想提出了支持自适应系统运行的动态绑定机制,设计了表述Agent如何适应环境变化的自适应策略描述语言SADL(self-adaptive strategy description language),开发了SADL的编译器和运行支撑环境.该方法将复杂自适应系统的自适应逻辑和业务逻辑相分离,通过SADL语言显式地描述系统的自适应特征,从而简化了复杂自适应系统的开发和维护.通过案例分析,阐述了如何基于上述方法来进行复杂自适应系统的开发,验证了方法的有效性.

复杂自适应多Agent系统的环境表示及感知

对自适应系统驻留环境的显式表示和有效感知是实现复杂自适应系统的前提,也是当前自适应系统研究面临的一项重要挑战.借助于组织学思想将自适应系统中的自主运行单元抽象为Agent,把复杂自适应系统视为多Agent组织,提出了基于动态绑定的自适应机制和构造框架;将环境作为一阶抽象,提供了对自适应多Agent组织的驻留环境进行抽象和描述的语言设施以及对环境进行有效感知的两种方法:基于事件发布-订阅和基于软传感器的方法;提出了支持软传感器与环境动态关联的思想和技术,使得复杂自适应系统的开发具有环境表示显式化、环境感知透明化的特征,所开发的软件系统易于维护和升级.介绍了实现上述机制、技术和语言设施的支撑平台SADE,并进行了案例分析以验证方法的可行性和有效性.

基于多Agent和动态逻辑制造单元的车间控制系统研究

根据敏捷化生产的要求 ,分析车间控制系统的多 Agent层次结构。提出动态逻辑制造单元的概念 ,用于组织车间制造系统资源 ,实现在动态多变的环境中车间制造系统快速重组、动态重构的能力。研究在动态逻辑制造单元的组织形式下 ,面向订单的生产调度的实现方法 。

Agent动态交互信任预测与行为异常检测模型

在agent理论中,信任计算是一个有意义的研究方向.然而目前agent信任研究都是以平均交互成功率来计算,较少考虑信任动态变化,因而准确预测和行为异常检测的能力不能令人满意.针对上述问题,以概率论为工具,按时间分段交互历史给出agent交互信任计算模型CMAIT;结合信任的变化率,给出信任计算的置信度和异常检测机制.实验以网上电子商务为背景,实验结果显示该计算模型的预测误差为TRAVOS的0.5倍,计算量也较少;既可用于对手历史行为的异常检测,防止被欺骗,又可用于对手未来行为的预测.改进了Jennings等人关于agent信任的工作.