Collaborative Research: Multivariable Fixed Order Controller Synthesis and Design from Data

协作研究：基于数据的多变量固定阶控制器综合与设计

• 批准号: 0927652
• 负责人: S. Bhattacharyya
• 金额: $ 22.58万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-10-01 至 2013-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0927652&HistoricalAwards=false
• 关键词: Collaborative; Research; Multivariable; Fixed; Order

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).This research aims to develop new fundamental theory and effective design methodologies to address practically important issues that existing control theories cannot effectively handle: specifically the proposal will develop methods for the design of fixed and low order controllers for multivariable systems which satisfy multiple design specifications and which are based on the measured data and not on models. This is a very realistic engineering problem that remains open despite significant progress in computer-aided design. The objective of feedback control system design is to precisely regulate physical quantities such as position, velocity, temperature, pressure, flow-rate and level in dynamic systems despite significant uncertainty and knowledge of the behavior of the underlying processes. The present proposal approaches the control design problem with a view to overcoming several outstanding challenges. These are a) the need to develop design methods which use measured data directly since mathematical models are unavailable for most systems b) the design of low order or low complexity controllers since the existing methods yield high order controllers which are often fragile or acutely sensitive and therefore unimplementable and c) designs which satisfy multiple user defined specifications. Preliminary results on integral and first order controllers look promising. The research should have a significant impact on control applications ranging from chemical processes, manufacturing systems, disk drives, missile and aircraft control, internet congestion control and biological control systems including genetic networks. In each of these applications models are scarcely available and few effective design techniques exist for the effective design of simple controllers.

该奖项是根据2009年美国复苏和再投资法案资助的（公法111-5）。本研究旨在开发新的基本理论和有效的设计方法，以解决现有控制理论无法有效处理的实际重要问题：具体地说，该建议将为满足多种设计规范的多变量系统开发固定和低阶控制器的设计方法并且它们基于测量数据而不是模型。这是一个非常现实的工程问题，尽管在计算机辅助设计方面取得了重大进展，但仍然没有解决。反馈控制系统设计的目的是精确地调节物理量，如位置，速度，温度，压力，流量和水平的动态系统，尽管显着的不确定性和知识的行为的基础过程。本建议的方法控制设计问题，以期克服几个突出的挑战。 这些是a）开发直接使用测量数据的设计方法的需要，因为数学模型对于大多数系统是不可用的; B）低阶或低复杂性控制器的设计，因为现有方法产生高阶控制器，其通常是脆弱的或非常敏感的，因此是不可实现的;以及c）满足多个用户定义的规范的设计。积分和一阶控制器的初步结果看起来很有希望。 该研究将对控制应用产生重大影响，包括化学过程，制造系统，磁盘驱动器，导弹和飞机控制，互联网拥塞控制和生物控制系统，包括遗传网络。在每一个这些应用模型几乎是可用的，几个有效的设计技术存在简单的控制器的有效设计。