Ito-Volterra Integral Approach to Optimal Filtering and Control of Processes with Continuous, Discrete and Delayed Measurements

Ito-Volterra 通过连续、离散和延迟测量实现最佳过滤和过程控制的整体方法

• 批准号: 0117300
• 负责人: Mikhail Skliar
• 金额: $ 24.55万
• 依托单位: University of Utah
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-01-01 至 2006-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0117300&HistoricalAwards=false
• 关键词: Ito; Volterra; Integral; Approach; Optimal

This research is mostly concerned with the problem of the optimal state estimation of continuous systems based on continuous and discrete measurements, subject to arbitrary, time-varying and a priori unknown time delays. The sampling rate of discrete measurements is allowed to vary in time in a priori unknown way. The optimal filter equation in this case must be continuous to reflect the continuous nature of the process, and to account for continuous measurements. This optimal filter will be subject to discontinuous inputs at the moment when discrete measurements become available. The innovation of the research is that (1) the problem is approached directly as a continuous problem with discontinuities without simplifying assumptions, and (2) the most general case of time-varying and a priori unknown delays in discrete and continuous measurements is studies. The aims of the proposed research are to:1. Develop the theory of optimal state estimation for continuous systems with discrete and continuous measurements;2. Extend the developed theory for the case when sampling rates of the discrete measurements are unknown and time varying;3. Extend the developed theory to include the case when both discrete and continuous measurements are subject to arbitrary, time varying and a priori unknown time delays;4. Reduce the general theoretical results of an integral approach to practically important cases of state space systems and systems with plant and measurement memory;5. Develop the software that implements the developed methods, and6. Test and compare the developed methods using simulation and experimental studies.Additional objectives are to lay the foundation for extending the proposed integral approach for the case of discontinuities of plant structure and parameters, constraints and inputs; to extend the results on nonlinear systems; and to study the application of the developed filtering methods to dual control problems.The research will include international and industrial collaboration.The estimation, based on available measurements, of variables characterizing processes and systems during their dynamic operation, is the fundamental problem in the variety of engineering and science areas. A special case of the estimation problem when it is desirable to estimate variables that are not directly measurable requires that we use the model of the process in the estimation procedure. A particular important case of the model-based estimation methods for the case of discrete and continuous measurements with time varying and generally unknown delays is the subject of the proposed approach. The method developed during this project will be applicable in such areas as state and parameter estimation for processes with manual sampling, human-triggered data acquisition and state estimation of remote processes with time delays in measurements and actuation introduced by non-deterministic properties of the information transport through the data network. The theoretical foundation developed in the course of this research will be relevant to practically relevant cases of linear dynamic systems with any combination of discrete and continuous measurements subject to arbitrary and time-varying time delays. The extension on the case of non-linear systems is also proposed.

本文主要研究了具有任意时变和先验未知时滞的连续系统的最优状态估计问题。 允许离散测量的采样率以先验未知的方式随时间变化。 在这种情况下，最佳滤波器方程必须是连续的，以反映过程的连续性，并考虑连续测量。 当离散测量变得可用时，该最佳滤波器将受到不连续输入的影响。 本文的创新之处在于：（1）将该问题直接作为具有不连续性的连续问题来处理，而不需要简化假设;（2）研究了离散和连续测量中时变和先验未知时滞的最一般情况。 本研究的目的是：1。发展了具有离散和连续量测的连续系统的最优状态估计理论;2.将已有的理论推广到离散测量采样率未知且时变的情况;3.扩展所开发的理论，包括离散和连续测量都受到任意，时变和先验未知的时间延迟的情况下;4。将积分方法的一般理论结果减少到状态空间系统和具有工厂和测量存储器的系统的实际重要情况;5.开发实现所开发方法的软件;使用仿真和实验研究来测试和比较所开发的方法。另外的目标是为扩展所提出的积分方法的基础，用于工厂结构和参数、约束和输入不连续的情况;扩展非线性系统的结果;并研究如何将已发展的过滤方法应用于双重控制问题。研究将包括国际和工业合作。在各种工程和科学领域中，基于可用的测量来估计表征过程和系统在其动态操作期间的变量是基本问题。 当需要估计不可直接测量的变量时，估计问题的特殊情况需要我们在估计过程中使用过程模型。 一个特别重要的情况下，基于模型的估计方法的情况下，离散和连续测量随时间变化，一般未知的延迟是所提出的方法的主题。 本项目期间开发的方法将适用于以下领域：手动采样过程的状态和参数估计、人为触发的数据采集和远程过程的状态估计，这些过程在测量和驱动过程中存在时间延迟，这些延迟是由通过数据网络传输的信息的不确定性引起的。 在这项研究的过程中开发的理论基础将是相关的线性动态系统的任何组合的离散和连续测量的任意和随时间变化的时间延迟的实际相关的情况。 对非线性系统的情形也作了推广。