【作者】 忻克非；

【导师】 King Yeung Yau； 孙优贤； 陈积明；

【作者基本信息】 浙江大学 ， 控制科学与工程， 2014， 博士

【摘要】 近年来,随着无线通信技术、传感器技术和微电子技术的迅猛发展,由无线传感器网络和网络控制系统发展而来的无线网络控制系统应运而生,它是一门由通信技术、网络技术、计算机技术以及控制理论等多方面相互交叉的学科。无线网络控制系统已经在越来越多的领域得到广泛应用,如工业过程、环境监测、农牧业应用、物联网和智能电网等,极大地方便了人们的生产和生活,因此受到国内外研究者的高度关注。资源优化问题是无线网络控制系统的核心问题之一,而无线网络控制系统中网络通信与控制性能的相互影响给该方面的研究带来了巨大挑战。现有针对无线网络控制系统中资源优化的研究目标大多仅考虑系统的某一方面,比如仅针对网络通信性能、系统状态估计性能或者闭环控制性能,而将上述几方面结合考虑并进行协同优化的方法和成果尚不完善。本文结合国内外最新的研究成果,考虑了通信、估计、控制三者的相互影响,并对三者进行协同优化。本文的主要工作和贡献可概括为以下几个方面：1.介绍了无线网络控制系统的产生以及应用背景,并概述了相关方面的研究现状。2.针对多个传感器节点的通信存在相互干扰的场景,以系统最优远端估计为目标,以实际的无线通信模型为基础,采用模型预测控制方法设计了一种传感器发送调度算法。并以仅存在两个传感器的简化系统为例,详细阐述了该调度算法的运行过程,并通过理论分析和仿真验证了该算法的有效性。3.针对多跳网络中的最优远端估计问题,为中继节点设计了一种能量有效的续传策略。首先根据中继节点计算能力和存储能力的不同提出了直接续传策略和本地处理-续传策略两种基本的续传策略,并对比了两者的估计性能以及系统能耗,然后结合两种策略的优势,设计了一种事件触发续传策略,使系统在较低的系统能耗下获得较好的估计性能。4.研究了无线网络控制系统中的最优控制器位置问题。考虑系统中传感器-控制器以及控制器-执行器两条链路的通信都均在随机丢包,将系统的闭环控制性能描述成关于数据包接收率的函数,并分别为标量系统和矢量系统设计了最优的控制器位置。5.考虑无线网络控制系统中的多目标定位应用,设计了能量有效的传感器节点唤醒策略。将压缩采样技术应用到无线网络控制系统的多目标定位中,首先根据上一步定位的结果设计了一种迭代的传感器节点唤醒策略,使当前时刻具有较高测量信噪比的传感器有更高的概率被唤醒,优化了系统中节点能量的使用效率；然后提出了一种IA-LSCS算法,进一步提高了定位精度,并证明该定位算法可以用来跟踪移动目标。最后对全文进行了总结,并展望了下一步的研究工作。更多还原

【Abstract】 With the rapid progress of wireless communication, wireless sensor node and microelectronics technologies in recent years, wireless networked control system (WNCS) which is evolved from wireless sensor networks (WSN) and networked control system (NCS), is arising. WNCS is an interdiscipline involved with communication technology, network technology, computing technol-ogy, control theorem and etc. It has been widely applied in various applications, such as industrial processes, environmental monitoring, agricultural applications, Cyber-physical systems (CPS) and smart grid. It has gained great attentions of global researchers for the convenience that it brings to the productivities and lives of human beings.Resource optimization is one of the fundamental topics in WNCS, and the interaction between network communication and close-loop control makes it a challenging problem. Most of existing works on the resource optimization in WNCS focus on one aspect among network communication, estimation or close-loop control performance. Nevertheless, the cooperative optimization of the above three aspects remain to be perfected. In this thesis, based on the latest results, the interaction between network communication, estimation and control is considered, and the cooperative opti-mization of them is studied in detail. The main work and contribution are summarized as follows.1. A brief literature review on WNCS and related works is provided.2. For the remote state estimation problem with wireless channel interference, under the real wireless communication model, a sensor transmission schedule is proposed based on Model Predictive Control (MPC) method. In particular, a two-sensor case is studied in detail and the analytical transmission schedule is developed, whose effectiveness is verified by theoretical analysis and numerical results.3. For the remote state estimation problem in multi-hop wireless communication, an energy-efficient data forwarding strategy is proposed. Firstly, two basic data forwarding strategies named Direct Forwarding Strategy (DFS) and Local process and Forwarding Strategy (LFS) are proposed, and then their estimation performance and energy cost are compared. Sec-ondly, to take the advantages of the above two strategies, a novel Event-triggered Forwarding Strategy (EFS) is developed, which is shown to achieve satisfactory estimation performance with low energy cost.4. The optimal controller location problem in WNCS is studied. With the consideration of random packet loss in both sensor-to-controller channel and controller-to-actuator channel, the close-loop control performance is formulated as a function of the packet reception rates of the two channels. Then the optimal controller location is then solved for both scalar system and vector system.5. For multi-target localization problem in WNCS, a sensor activation algorithm is proposed. Compressive Sampling (CS) is using in multi-target localization. In every time step, an it-erative activation algorithm is run on each sensor node based on the last localization results, which will make the particular sensor nodes with larger SNR be activated with higher prob-ability to measure the signals from targets. This will optimize the use of sensor energy in WNCS. Then the IA-LSCS algorithm is proposed to further improve the localization accu-racy, which is shown to be well applied in tracking mobile targets.In the end, the thesis is concluded and some future research works are discussed.更多还原