多率非线性系统的网络化控制及其应用

Network control systems (NCSs) have several advantages, such as reduced system wiring, increased system agility, and ease of system diagnosis and maintenance. Consequently, networked control is the current trend for industrial automation and has application in a broad range of areas such as industrial control processes, intelligent transportation systems and so on. In the practical application of NCSs, the controlled plant is usually nonlinear, there exist a variety of sampled-data sensors, and the network bandwidth is limited. Therefore, how to choose a good real-time sampling method and to design a network-resource-saved transmission scheme is of theoretical significance for improving the operating mechanism of NCSs. However, there have been few results available in the published research. By introducing a classification strategy of multiple sampling rates of various sensors to determine a multi-rate sampling method and constructing an event-triggered transmission scheme to determine whether or not sampled-data should be transimtted, this project will investigate the control problem for a class of nonlinear NCSs which can be described by T-S fuzzy models. In this project, by applying the classification strategy of multiple sampling rates and constructing an effective event-triggered transmission scheme, the mathematical models of event-triggered based single-rate nonlinear NCSs, multi-rate nonlinear NCSs and event-triggered based multi-rate nonlinear NCSs will be established respectively, and some design methods of the networked controller or networked switched cotroller will be proposed to meet the system performances. When a single-rate sampling and a multi-rate sampling are available for a nonlinear NCS, it will be shown that the multi-rate nonlinear NCS is more superior to the single-rate nonlinear NCS from the view of system performances. Finally, these research results will be applied to the stable control for an autonomous platoon in a network environment. This project will not only broaden the research field of NCSs, but also provide some effective design approaches for their practical applications.

网络化控制系统(NCSs)已成功应用于工业控制过程、智能交通系统等领域，并展现出广阔的应用前景。在NCSs的应用中，通常会遇到被控对象是非线性的、多种采样传感器并存以及网络带宽受限等情形。然而，如何选择实时性好的采样方式和设计节约网络资源的传输方案来改进NCSs的运行机制的研究工作还很少。本项目针对T-S模糊模型表示的非线性系统，引入不同传感器多采样率的分类策略来确定多率采样方式，构建一个有效的事件触发传输方案来决定采样数据是否传输，分别研究基于事件触发的单率非线性系统、多率非线性系统和基于事件触发的多率非线性系统的网络化控制问题，提出满足某些系统性能的控制器或切换控制器的设计方法。在单率采样和多率采样都容许情形下，验证多率非线性NCSs在系统性能方面优于单率非线性NCSs。最后，将这些研究成果应用于网络环境下自主车队稳定控制。本项目将拓宽NCSs的研究领域，并为其应用提供有效的设计方法。

在网络化控制系统的应用中，存在多速率采样传感器组和网络带宽受限等现象。本项目主要研究带有事件触发传输方案和多率采样的非线性系统的网络化控制问题。主要研究成果包括：(1) 首次提出了一种新的事件触发传输方案来减少网络带宽的使用，并建立了网络环境下隶属度函数偏差的一个新颖的引理，显式地刻画了隶属度函数的偏差界和网络控制系统的最大容许等价时延界的关系。通过建立非线性网络化控制系统或网络化跟踪控制系统的数学模型，给出了隶属函数偏差界依赖的模糊控制器和事件触发方案的联合设计方法。通过理论和数值仿真证明了利用隶属度函数偏差界可以获得更小保守性的性能分析和控制器设计结论，并验证了事件触发传输方案能够降低网络的数据传输率；(2) 针对不能被无时滞控制器镇定的线性系统、模糊系统和非周期采样控制系统，分别建立了主动网络化采样控制系统和网络化输出跟踪控制系统的数学模型，给出了相应主动网络化控制器的设计方法；(3) 通过引入有效的不同传感器多采样率的分类策略，构建了能够同步对象和观测器(或控制器)的多速率采样数据的匹配机制，分别建立了多率采样网络化控制系统和网络化滤波误差系统的数学模型，给出多率采样系统的网络化控制器和带有多速率采样的时滞系统的网络化滤波器的设计方法、以及事件触发传输方案与网络化滤波器的联合设计方法，并通过仿真验证了多率非线性NCSs 在性能等方面优于相应的单率非线性 NCSs；(4) 给出了智能车队跟随系统的主动干扰抑制控制器的设计方法，并构建了网络环境下的自主车队稳定控制系统的仿真平台。本项目拓宽了NCSs 的研究领域，并为其应用提供有效的设计方法。