非线性系统和网络控制系统的迭代学习控制律的收敛性态研究

项目名称： 非线性系统和网络控制系统的迭代学习控制律的收敛性态研究

项目编号： No.61273135

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 自动化技术、计算机技术

项目作者： 阮小娥

作者单位： 西安交通大学

项目金额： 76万元

中文摘要： 针对于非线性连续系统，研究PID型、r-1阶-r阶导数型、时间超前型、前馈补偿型等迭代学习控制律的设计机理和在Lebesgue-p范数度量意义下的收敛性态和收敛速度等，探索拟李雅普诺夫泛函法分析迭代学习控制律的收敛性的理论；对于网络控制系统，利用神经网络等数据挖掘技术，研究网络时延的辨识方法，设计时间超前型迭代学习控制律，理论论证控制律的收敛性态，分析网络时延对系统的稳定性和迭代学习控制律的收敛性的影响；对于网络控制系统，研究丢包数据的样条插值估计法、最小二乘意义下的数据拟合估计法、时间序列分析估计法等技术，构建有效的迭代学习控制律，论证控制律的收敛性态；研究网络时延的阈值变化和数据丢包率的变化对网络化迭代学习控制系统跟踪性能的影响的评价方法和评价结果等；研究连续系统和离散系统关于系统动力学描述、学习控制律的等效性和收敛条件的等价性等。数字仿真和实验验证理论分析的正确性和控制律的有效性等。

中文关键词： 迭代学习控制；收敛性；非线性；网络控制系统；通信时延与丢包

英文摘要： For nonlinear continuous systems, the project firstly studies the Proportional-Integral-Derivative-type,(r-1)-r-order Derivative-type,time leading-type and feedforward compensated-type iterative learning control （ILC）schemes and their convergence characteristics and convergence speeds, in the sense that the tracking error is measured in the form of Lebesgue-p norm. It also explores a kind of convergence analysis theory of quasi-Lyapunov functional method. Secondly, for networked control systems, by means of data digging techniques such as neural network, the project exploits the methods of identifying the network induced time-delay, constructs a time leading ILC law, derives its convergence characteristics and analyzes the impact of the time-delay on the system stability and ILC convergence, etc. Further, for the networked control systems, the project develops methods such as spline insertation, data fitting in the sense of least square as well as time sequence analysis so as to estimate the value of dropped data. Based on the estimated data, the project designates effective iterative learning updating laws and derives their convergence properties. Next, the project raises techniques to evaluate the influence of the network induced time-delay range and data dropout rate on the tracking performance. Finally, the

英文关键词： iterative learning control；convergence；nonlinear systems；netwoked control systems；communication delay and data dropout