Coordinated dispatching of proximity sensors for the surveillance of manoeuvring targets

The surveillance of a manoeuvring target with multiple sensors in a coordinated manner requires a method for selecting and positioning groups of sensors in real time. Herein, the principles of dispatching, as used for the effective operation of service vehicles, are considered. The object trajectory is first discretized into a number of demand instants (data acquisition times), to which groups of sensors are assigned, respectively. Heuristic rules are used to determine the composition of each sensor group by evaluating the potential contribution of each sensor. In the case of dynamic sensors, the position of each sensor with respect to the target is also specified. Our proposed approach aims to improve the quality of the surveillance data in three ways: (1) The assigned sensors are manoeuvred into “optimal” sensing positions, (2) the uncertainty of the measured data is mitigated through sensor fusion, and (3) the poses of the unassigned sensors are adjusted to ensure that the surveillance system can react to future object manoeuvres. If a priori target trajectory information is available, the system performance may be further improved by optimizing the initial pose of each sensor off-line. The advantages of dispatching dynamic sensors over similar static-sensor systems are demonstrated through comprehensive simulations.     

Soft computing in big data intelligent transportation systems

The academic and industry have entered big data era in many computer software and embedded system related fields. Intelligent transportation system problem is one of the important areas in the real big data application scenarios. However, it is posing significant challenge to manage the traffic lights efficiently due to the accumulated dynamic car flow data scale. In this paper, we present NeverStop, which utilizes genetic algorithms and fuzzy control methods in big data intelligent transportation systems. NeverStop is constructed with sensors to control the traffic lights at intersection automatically. It utilizes fuzzy control method and genetic algorithm to adjust the waiting time for the traffic lights, consequently the average waiting time can be significantly reduced. A prototype system has been implemented at an EBox-II terminal device, running the fuzzy control and genetic algorithms. Experimental results on the prototype system demonstrate NeverStop can efficiently facilitate researchers to reduce the average waiting time for vehicles.     

Metropolitan intelligent surveillance systems for urban areas by harnessing IoT and edge computing paradigms

Recent technological advances led to the rapid and uncontrolled proliferation of intelligent surveillance systems (ISSs), serving to supervise urban areas. Driven by pressing public safety and security requirements, modern cities are being transformed into tangled cyber‐physical environments, consisting of numerous heterogeneous ISSs under different administrative domains with low or no capabilities for reuse and interaction. This isolated pattern renders itself unsustainable in city‐wide scenarios that typically require to aggregate, manage, and process multiple video streams continuously generated by distributed ISS sources. A coordinated approach is therefore required to enable an interoperable ISS for metropolitan areas, facilitating technological sustainability to prevent network bandwidth saturation. To meet these requirements, this paper combines several approaches and technologies, namely the Internet of Things, cloud computing, edge computing and big data, into a common framework to enable a unified approach to implementing an ISS at an urban scale, thus paving the way for the metropolitan intelligent surveillance system (MISS). The proposed solution aims to push data management and processing tasks as close to data sources as possible, thus increasing performance and security levels that are usually critical to surveillance systems. To demonstrate the feasibility and the effectiveness of this approach, the paper presents a case study based on a distributed ISS scenario in a crowded urban area, implemented on clustered edge devices that are able to off‐load tasks in a “horizontal” manner in the context of the developed MISS framework. As demonstrated by the initial experiments, the MISS prototype is able to obtain face recognition results 8 times faster compared with the traditional off‐loading pattern, where processing tasks are pushed “vertically” to the cloud.     

Broadcast control of radar surveillance systems for unexpected drones

In this paper, we propose a new antidrone surveillance system with multiple vehicles and bistatic radars whose antennas are mounted in each vehicle. The proposed system is based on the broadcast control technique recently proposed. We show that our method provides the optimal formation in terms of the received signal level of echoes from the drone intruders, without the information about the relation among the signal level, the locations of vehicles, and the locations of intruders. The proposed system is demonstrated by numerical simulation.     

Development of an intelligent agent system for collaborative mold production with RFID technology

This paper presents a multi-agents system called agent-based collaborative mold production (ACMP) system. ACMP supports the collaborative and autonomous mold manufacturing outsourcing processes. The mold manufacturing outsourcing processes involve not only many manufacturing sequences but also many collaboration partners. ACMP provides autonomous features to handle three major tasks in outsourcing. They are vendor selection, task selection, and real-time outsourcing task progress tracking. This research applies the analytic hierachy process (AHP) decision models to solve the vendor selection and task selection problems. In addition, radio frequency identification (RFID) technology is adopted to provide a real-time tracking capability for remote collaboration, control and monitoring among outsourcing partners.     

Control of complex distributed systems with distributed intelligent agents

Control of spatially distributed systems is a challenging problem because of their complex nature, nonlinearity, and generally high order. The lack of accurate and computationally efficient model-based techniques for large, spatially distributed systems leads to challenges in controlling the system. Agent-based control structures provide a powerful tool to manage distributed systems by utilizing (organizing) local and global information obtained from the system. A hierarchical, agent-based system with local and global controller agents is developed to control networks of interconnected chemical reactors (CSTRs). The global controller agent dynamically updates local controller agent’s objectives as the reactor network conditions change. One challenge posed is control of the spatial distribution of autocatalytic species in a network of reactors hosting multiple species. The multi-agent control system is able to intelligently manipulate the network flow rates such that the desired spatial distribution of species is achieved. Furthermore, the robustness and flexibility of the agent-based control system is illustrated through examples of disturbance rejection and scalability with respect to the size of the network.     

GIS在智能交通系统交叉口监控中的应用研究

研究了智能交通系统中城市道路交叉口监控问题.着重针对交叉口监控中数据量大,且无法及时进行分析,动态调度和实时控制的问题进行了调查.通过对交叉口监控中大量数据的分析和整合,提出了利用地理信息系统和数据库有效解决海量数据存储和分析的方法.首先讨论了基于海量数据库的地理信息系统的技术框架,提出了一种基于Intergraph Geo-Media的交叉口交通监测模型以及系统实现方法,提高交通管理效率和城市道路利用率,接着探讨了基于GIS的智能交通交叉口监控系统亟需解决的问题.     

石油勘探开发数据服务系统

为满足石油工业上游勘探开发业务研究和方案设计对数据的特殊需求, 采用多数据源集成技术、数据分类与搜索技术、系统服务功能定制技术、数据使用授权与安全控制等技术, 实现了对石油勘探开发不同类型数据源、多数据类、海量数据, 在一个系统环境下访问和下载. 解决了国外、国内同类系统只局限单一或几类数据类型的访问的技术瓶颈.     

一种小型集散控制系统的研制

介绍了一种小型集散控制系统在工程控制领域中的应用实例 ,给出了实现该系统的原理框图 ,并详细介绍了各部分的作用和具体实现技术     

Adaptive intelligent control of aircraft systems with a hybrid approach combining neural networks, fuzzy logic and fractal theory

We describe in this paper a hybrid method for adaptive model-based control of nonlinear dynamic systems using neural networks, fuzzy logic and fractal theory. The new neuro-fuzzy-fractal method combines soft computing techniques with the concept of the fractal dimension for the domain of nonlinear dynamic system control. The new method for adaptive model-based control has been implemented as a computer program to show that the neuro-fuzzy-fractal approach is a good alternative for controlling nonlinear dynamic systems. It is well known that chaotic and unstable behavior may occur for nonlinear systems. Normally, we will need to control this type of behavior to avoid structural problems with the system. We illustrate in this paper our new methodology with the case of controlling aircraft dynamic systems. For this case, we use mathematical models for the simulation of aircraft dynamics during flight. The goal of constructing these models is to capture the dynamics of the aircraft, so as to have a way of controlling this dynamics to avoid dangerous behavior of the aircraft dynamic system.     

A description of dynamic behavior of sensory/motor systems with fuzzy symbolic dynamic systems

This paper presents a model of continuous sensory/motor systems for autonomous agents in naviga-tion problems. The Markov environmental model and sequential plan are extended with fuzzy sets, which present the mathematical transformation from discrete state space to continuous state space. The extended fuzzy environmental model and fuzzy sequential knowledge allow the identification of continuous sensory/motor systems with a gradient descent-based parameter estimation algorithm. A simulation demonstrates the feasibility of the proposed method. This work was presented, in part, at the Fourth International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–22, 1999     

The role of the New Zealand forest industry injury surveillance system in a strategic ergonomics,safety and health research programme

Forestry is among the most hazardous of all industry sectors internationally. In New Zealand, highest work-related morbidity and mortality incidence rates are found in the logging sector. The New Zealand Forest Industry Accident Reporting Scheme (ARS) is a forestry injury surveillance system maintained by the Centre for Human Factors and Ergonomics (COHFE). The paper highlights the pivotal role of an industry-wide injury surveillance system in an industry-specific strategic research programme, giving examples of the use of ARS data in identification of priority areas for ergonomics, safety and health research attention, for safety awareness feedback to the industry, and in the evaluation of injury countermeasures. An analysis of injury patterns and trends for one high-risk forestry operation (skid work) is presented to illustrate both the capabilities and limitations of the ARS in its present stage of development.     

基于多源数据整合的河湖水质智能应用研究

为改善上海市河道水环境,针对现有河湖水质存在的问题,依靠信息化和数字化技术,汇聚各类水质相关数据,开展数据整合与分析,推出河道水质变化三级报警预警,建立相应业务处置机制和流程,探索河湖水质智能化应用,重点研究河湖水质数据监测、变化趋势分析、波动报警预警、整改处置和结果反馈等5个环节闭环管理.通过河湖水质智能应用研究,并在上海市河长制办公室工作平台和城市运行"一网统管"水务专题中进行实际应用.实际应用表明:河湖水质智能应用可有效发挥作用,强化对河湖水质恶化等问题的持续跟踪和有效监督,提高河湖水质治理效率,推进河湖协同治理,有效改善河湖水环境质量.     

WinAC控制器在污水处理控制系统中的应用

主要介绍了以WinAC控制器构成的过程控制系统,详细描述了系统的结构。利用STEP7软件完成了硬件组态和过程控制程序的编写。该系统集成了PLC和PC的优点,具有可靠性高、易维护、可扩展、便于进行二次开发等特点。     

自动化科学与技术发展方向

本文结合中国自动化科学与技术的发展状况和中国绝大多数大学设有自动化专业的现状,借鉴自动化科学与技术发展历程中的成功经验,结合国家社会经济发展和国家安全对自动化系统的未来需求,以生产制造系统、重要运载工具和人参与的信息物理系统为主要对象,以自动化系统的发展方向—智能自主控制系统、智能优化决策系统和智能优化决策与控制一体化系统的愿景功能为目标,以研究实现愿景功能的建模、控制与优化新算法和新的自动化系统的设计方法和实现技术以及结合重大应用领域开展的应用研究为主线,提出了自动化科学与技术的发展方向,并结合新兴应用领域对自动化科学与技术的需求与挑战,提出了未来自动化科学与技术的发展方向.     

水雷用定深测控系统的设计和实现

提出并实现了一种集开关控制、拉力测试和深度测试三种功能于一体的定深测控系统，着重介绍了系统结构、功能及软件实现。系统采用定深测控装置完成数据的精确采集及开关控制要求，利用终端数据处理软件处理回收的数据，图形化显示拉力、深度的变化曲线。运行结果表明：系统工作可靠，具有很好的效果。     

Consensus of multi‐agent systems with fixed inner connections

This paper characterizes a unified consensus region for multi‐agent systems, where there exist fixed physical connections with information exchange. The notions of synchronization region in complex networks and consensus region in multi‐agent systems can be explained under this unified framework. The effect of the coupling terms on the consensus regions in different situations is analyzed specifically. Furthermore, necessary and sufficient conditions for consensus of agents under both distributed state feedback and observer‐based output feedback control are established. On the basis of a parameter‐dependent Lyapunov function, a 2‐step controller design procedure is proposed, which can reduce the conservativeness to some extent in comparison with the conventional direct Lyapunov method. In addition, for the case with disturbance, the robustness of the system is investigated. Finally, some numerical examples are presented to illustrate the theoretical results.     

Consensus of multiple double‐integrator agents with intermittent measurement

This paper is concerned with consensus problems in directed networks of multiple agents with double‐integrator dynamics. It is assumed that each agent adjusts its state based on the information of its states relative to its neighbors at discrete times and the interaction topology among agents is time‐varying. Both synchronous and asynchronous cases are considered. The synchrony means that each agent's update times, at which it obtains new control signals, are the same as the others', and the asynchrony implies that each agent's update times are independent of the others'. In the synchronous case, the consensus problem is proved to be equivalent to the asymptotic stability problem of a discrete‐time switched system. By analyzing the asymptotic stability of the discrete‐time switched system, it is shown that consensus can be reached if the update time intervals are small sufficiently, and an allowable upper bound of update time intervals is obtained. In the asynchronous case, the consensus problem is transformed into the global asymptotic stability problem of a continuous‐time switched system with time‐varying delays. In virtue of a linear matrix inequality method, it is proved that consensus can be reached if the delays are small enough, and an admissible upper bound of delays is derived. Simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2009 John Wiley & Sons, Ltd.     

Distributed containment control of multi‐agent systems with general linear dynamics in the presence of multiple leaders

This paper considers the containment control problems for both continuous‐time and discrete‐time multi‐agent systems with general linear dynamics under directed communication topologies. Distributed dynamic containment controllers based on the relative outputs of neighboring agents are constructed for both continuous‐time and discrete‐time cases, under which the states of the followers will asymptotically converge to the convex hull formed by those of the leaders if, for each follower, there exists at least one leader that has a directed path to that follower. Sufficient conditions on the existence of these dynamic controllers are given. Static containment controllers relying on the relative states of neighboring agents are also discussed as special cases. Copyright © 2011 John Wiley & Sons, Ltd.     

城市智能交通系统技术发展现状及趋势

城市化的快速发展带来一系列的交通问题,智能交通系统(Intelligent Transportation Systems,ITS)是解决交通问题的有效途径之一。本文主要介绍了智能交通系统的概念与内涵、我国城市智能交通系统技术发展与智能交通管控系统应用现状,在上述内容的基础上,总结了我国城市智能交通系统未来的发展趋势。