Feasible Formation of Coalitions Among Autonomous Agents in Nonsuperadditive Environments

Cooperating and sharing resources by creating coalitions of agents are important ways for autonomous agents to execute tasks and to maximize payoff. Such coalitions will form only if each member of a coalition gains more by joining the coalition than it could gain otherwise. There are several ways of creating such coalitions and dividing the joint payoff among the members. In this paper we present algorithms for coalition formation and payoff distribution in nonsuperadditive environments. We focus on a low-complexity kernel-oriented coalition formation algorithm. The properties of this algorithm were examined via simulations. These have shown that the model increases the benefits of the agents within a reasonable time period, and more coalition formations provide more benefits to the agents.
     

Coalition formation in weighted simple-majority games under proportional payoff allocation rules

In this paper, we introduce a simple coalition formation game in the environment of bidding, which is a special case of the weighted majority game （WMG）, and is named the weighted simple-majority game （WSMG）. In WSMG, payoff is allocated to the winners proportional to the players powers, which can be measured in various ways. We define a new kind of stability： the counteraction-stability （C-stability）, where any potential deviating players will confront counteractions of the other players. We show that C-stable coalition structures in WSMG always contains a minimal winning coalition of minimum total power. For the variant where powers are measured directly by their weights, we show that it is NP-hard to find a C-stable coalition structure and design a pseudo-polynomial time algorithm. Sensitivity analysis for this variant, which shows many interesting properties, is also done. We also prove that it is NP-hard to compute the Holler-Packel indices in WSMGs, and hence in WMGs as well.     

A differential pursuit/evasion game of capture between an omnidirectional agent and a differential drive robot,and their winning roles

This paper addresses a differential pursuit/evasion game. The players are an omnidirectional agent (OA) and a differential drive robot (DDR). They move in an obstacle-free environment; the DDR is faster than the OA but it can only change its motion direction up to a bounded rate. First, we analyse the scenario in which the OA has as objective to capture a DDR in minimum time and the DDR wants to retard the capture as long as possible. We present the time optimal motion primitives of the players to achieve their goals. Later, we allow the agents to change the roles, namely, the DDR is allowed to play as the pursuer and the OA is allowed to play as the evader. This later analysis allows one to establish which is the winner role for each agent, based only on the initial position of the players and their maximum speed.     

Assessment of the interaction between the Canadian Regional Climate Model and lake thermal–hydrodynamic models

This paper describes our preliminary assessment of the system requirements (data, interface and process) for implementation of terms describing lake effects in the Canadian Regional Climate Model. We demonstrate test results for one-dimensional (1-D) and three-dimensional (3-D) models for lake hydrodynamics that have been tested and prepared for interfacing with atmospheric circulation models. We discuss the use of a physical interface model, Canadian Land Surface Scheme (CLASS), that is under consideration for the air–water interface. Our preliminary assessment indicates that it is technically feasible to apply the combination of small shallow lake (slab) model, 1-dimensional vertical model and 3-dimensional circulation model (for very large lakes), together with the current land–air linkage used in regional climate modelling in Canada. Whether we can discern the necessary conditions for invoking each of the models to the lakes present in individual regional climate grid cells is still to be determined.     

An Integrated Software Environment For Powertrain Feasibility Assessment Using Optimization And Optimal Control

With the increase in automotive powertrain complexity, an upfront assessment of powertrain capability in meeting its design targets is important early on in the development programs. The optimization of control policy based on powertrain simulation models can facilitate this assessment and establish limits of achievable performance for a given powertrain configuration and parameters. The paper discusses several computational optimization and user interface solutions for deploying a numerical optimal control approach in a user‐friendly software environment.     

降阶模型误差对输电系统最优励磁控制的微动态稳定鲁棒性的影响

本文探讨了“串级阵阶模型误差”(包括控制回路中的惯性环节)对线性二次型(LQ)最优控制的稳定鲁棒性的影响。指出这种模型误差是造成LQ最优控制稳定鲁棒性差的一类重要因素。然后结合输电系统的实际情况分析计算了降阶模型误差对最优励磁控制的微动态稳定鲁棒性的影响。结果表明,被略去的小惯性时间常数对最优励磁控制的微动态稳定鲁棒性有较大的影响。     

Optimistic Value Model of Indefinite LQ Optimal Control for Discrete‐Time Uncertain Systems

Uncertainty theory is a branch of mathematics which provides a new tool to deal with the human uncertainty. Based on uncertainty theory, this paper proposes an optimistic value model of discrete‐time linear quadratic (LQ) optimal control, whereas the state and control weighting matrices in the cost function are indefinite, the system dynamics are disturbed by uncertain noises. With the aid of the Bellman's principle of optimality in dynamic programming, we first present a recurrence equation. Then, a necessary condition for the state feedback control of the indefinite LQ problem is derived by using the recurrence equation. Moreover, a sufficient condition of well‐posedness for the indefinite LQ optimal control is given. Finally, a numerical example is presented by using the obtained results.     

Ontology engineering in provenance enablement for the National Climate Assessment

The National Climate Assessment of the U.S. Global Change Research Program (USGCRP) analyzes and presents the impacts of climate change on the United States. The provenance information in the assessment is important because the assessment findings are of great public and academic concern and are used in policy and decision-making. By applying a use case-driven iterative methodology, we developed information models and ontology to represent the content structure of the recent National Climate Assessment draft report and its associated provenance information. We tested the ontology by using it in pilot systems serving information about instances of chapters, scientific findings, figures, tables, images, datasets, references, people, and organizations, etc. in the draft report, as well as interrelationships among those instances. The results successfully help users trace provenance in the draft report, such as finding all the journal articles from which a figure in the report was derived. The provenance information in our work was maintained in the context of the “Web of Data”. In addition to the pilot systems we developed, other tools and services are also able to retrieve and utilize the provenance information. Our work is part of a Global Change Information System coordinated by the USGCRP that will eventually cover provenance information for the entire scope of global change research. Such a system will greatly increase understanding, credibility and trust in the global change research and foster reproducibility of scientific results and conclusions.     

并行I/O技术在气候数值模式中的应用研究

在气候变化数值模拟工作中,气候数值模式运行效率主要受到计算效率和I/O效率的共同影响。目前,模式计算部分已经基本实现并行,计算效率显著提升。随着气候数值模式时空分辨率的提高,对I/O效率的需求也不断增加,数据并行I/O技术已经成为提高模式整体运行效率的有效方法之一。文中深入分析了BCC_AGCM模式串行I/O算法及NetCDF数据结构特点,采用基于MPI-IO的高层I/O库对模式I/O算法进行并行优化,优化后可支持多类气象要素并行输出,输出效率明显提升。为我国应对气候变化数值模式的运行效率优化工作,进行了有益的技术探索和积累。     

Formation Potential Field for Trajectory Tracking Control of Multi-Agents in Constrained Space

In this paper, a novel Formation Potential Field method is proposed for the multi-agent formation control. The objective is to control a group of agents to automatically generate and maintain a specific formation while avoiding internal collisions and collisions with spatial constraints. A Formation Potential Field is designed combining multiple local attractive potential fields with multiple local repulsive potential fields. To further relax requirements of agents' initial positions and enhance the robustness, a global attractive potential field is added outside the influence range of the local Formation Potential Field. The optimality of the proposed scheme in formation time is analysed as well as illustrated by contrast simulation results. Following the design of the Formation Potential Field, two controllers are proposed accordingly to achieve a stable dynamic formation during the process of trajectory tracking, while the saturation effect of input is taken into account. Furthermore, a collision avoidance strategy based on artificial potential field and Dirac delta function is applied to locally modify the original trajectory of the virtual leader such that agents can avoid collisions with unexpected spatial constraints while maintaining the given formation. Simulation results are presented to illustrate the performance of proposed approaches.     

利用遥感监测长江三角洲森林植被物候对气候变化的响应

植物的物候与气候等环境因素息息相关,是指示气候与自然环境变化对生态影响的重要指标。目前,气候变暖日益为人所关注,使用遥感技术研究植物物候与气候变化之间的关系具有重要的意义。监测人口密度高和城市经济发达地区的植物物候对气候变暖的响应,可以揭示区域热环境变化及其产生的生态效应。本研究选取长江三角洲地区为研究区域,使用SPOT卫星VGT传感器的长时间NDVI数据序列,对经济发达区域森林植被的NDVI序列进行非对称性高斯函数拟合法平滑处理,并提取与研究其物候特征,发现①NDVI与气温具有较强相关性,随气候变暖,森林植被NDVI年均值有增加趋势;②森林植被生长活跃期起始日期提前,终止日期延后,时长有明显的延长趋势,生长活跃期内NDVI有所增加;③森林植被NDVI极大值与极小值出现日期均明显提前,NDVI极大值有增大趋势,而极小值呈下降趋势,年内极差增加,NDVI增长期缩短,衰落期延长;④森林植被在春、夏两季NDVI均值有所增长,秋季无明显变化,冬季略有降低。     

流程工业最优生产控制的递阶流率模型

基于流程工业生产系统特性,构造新的递阶流率控制模型,对目标泛函的积分上限重新定义,引入新的状态变量,在最优生产时间标准下给出了递阶滚动优化算法框架.仿真结果表明该生产策略更易于工程实现.     

Integrated modelling of urban spatial development under uncertain climate futures: A case study in Hungary

To provide fundamental decision support information for climate risk assessment in Hungary, an urban spatial development model of land cover change and population age structure dynamics was developed and applied to local integrated scenarios of climate change and stakeholder-derived socio-economic change. The four integrated scenarios for Hungary produced contrasting projections for urban patterns to 2100, but peri-urbanisation around Budapest was estimated to occur under all scenarios, together with a decline in working age population in the centres of the capital and major towns. This suggests that future urban planning needs to take into consideration the potential for underutilised urban infrastructure in the centre of the capital and pressures for social service provisioning in its outskirt. The integrated scenarios and model developed can be used in future studies to test the effectiveness of inter-sectoral policy responses in adapting urban planning to multiple climate and socio-economic challenges.     

人工气候室照度神经网络控制系统的研究

人工气候室光照系统具有复杂的非线性,不确定性,滞后性,常规控制难以达到较好的效果。针对这一问题,采用神经网络的PID控制,可实现对系统的在线辨识和控制;为克服局部最小问题。采用遗传算法时神经网络权阈值进行优化。仿真结果表明,该系统控制效果好,稳态精度高,响应较快,动态性能好,超调量较小,完全满足控制要求。     

新型煤矿综合监控系统

介绍了改造后的KJ95型煤矿综合监控系统。改造后的系统结构、软件及分站等主要设备的功能都有了进一步的完善和提高 ,完全能满足当前矿井安全生产和现代化管理的要求     

人机控制系统中操纵者两级控制模型

本文应用模糊理论和人工智能技术,提出和建立了一种操纵者两级控制模型,该模型由上层协调级和下层运行控制级组成,分别用于描述人的监控、协调及其它智能性活动和人的控制行为(技能性活动)。     

A Model Predictive Scheduling Algorithm in Real-Time Control Systems

The ineffective utilization of power resources has attracted much attention in current years. This paper proposes a real-time distributed load scheduling algorithm considering constraints of power supply. Firstly, an objective function is designed based on the constraint, and a base load forecasting model is established when aggregating renewable generation and non-deferrable load into a power system, which aims to transform the problem of deferrable loads scheduling into a distributed optimal control problem. Then, to optimize the objective function, a real-time scheduling algorithm is presented to solve the proposed control problem. At every time step, the purpose is to minimize the variance of differences between power supply and aggregate load, which can thus ensure the effective utilization of power resources. Finally, simulation examples are provided to illustrate the effectiveness of the proposed algorithm.      

An Integrated Approach to Scheduling in Safety-Critical Embedded Control Systems

This paper describes an approach that has been developed over a number of years for the job of scheduling systems and providing evidence that timing requirements are met. The approach has been targeted at the safety-critical systems domain, and more specifically the development of control systems for jet engines. The work provides a usable computational model that supports the reuse of legacy systems. In addition, timing analysis has been developed that features low pessimism, low computational complexity and that is robust to change. The contributions of this paper are to show how standard timing analysis is often insufficient for real systems, presenting extensions to the standard analysis to give an integrated approach to verification, and providing a case study that demonstrates the appropriateness and benefits of the overall technique.     

Design method for a new control system for an autonomous underwater vehicle using linear matrix inequalities

The independent administrative corporation Japan Agency for Marine–Earth Science and Technology (JAMSTEC) has developed a small light autonomous underwater vehicle (AUV) named marine robot experimental 1 (MR-X1).¹ The motion control of MR-X1 is considered in this article. Since the dynamics of MR-X1 mainly depends on its own speed, the motion control is a nonlinear control system. We propose a new controller design method for this system using linear matrix inequalities (LMIs). This algorithm gives a solution as a linear matrix inequality, and can be adapted to solve many LMIs simultaneously. LMIs can be obtained by substituting several speeds into the dynamics of the MR-X1. The proposed controller, which can be derived from the solution of the LMIs, was adapted to MR-X1 and showed good performance in experiments. This work was presented in part at the 11th International Symposium on Artificial Life and Robotics, Oita, Japan, January 23–25, 2006