ITR/SY (CISE): Verification and Supervisory Control of Hybrid Embedded Systems

ITR/SY (CISE)：混合嵌入式系统的验证和监督控制

• 批准号: 0113131
• 负责人: Panos Antsaklis
• 金额: $ 36.67万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-01 至 2006-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0113131&HistoricalAwards=false
• 关键词: ITR; SY; CISE; Verification; Supervisory

Project AbstractProposal #0113131Antsaklis, PanosU of Notre DameThe goals of this project are to develop algorithms and prototype software for the verification and supervision of hybrid embedded control systems; also for the identification of hybrid system models. This project is developing supervisory processors to supervise and control in real time the operation of large number of control processors interacting with the outside world. The control processors interact with the physical world while the supervisory processors are responsible for monitoring and maintaining the health of thedistributed control system in a highly autonomous and fault-tolerant manner. The innovative characteristics of this project are as follows: 1) the development and application of novel discrete event supervisory methods to supervise hybrid embedded systems; 2) the development and application of novel approaches to the verification and supervision of hybrid, piece-wise linear systems; 3) the development of theory and algorithms to extend these results to a class of nonlinear hybrid systems; and, 4) the development of novelmodel identification methodologies and algorithms for hybrid systems. The project's approach will improve the ability of hybrid embedded control systems to deal with high complexity, undecidability and nonlinearity.

项目摘要该项目的目标是开发算法和原型软件，用于混合嵌入式控制系统的验证和监督；也用于混合系统模型的识别。该项目正在开发监控处理器，对大量与外界交互的控制处理器的运行进行实时监控。控制处理器与物理世界交互，而监控处理器以高度自治和容错的方式负责监控和维护分布式控制系统的健康。该项目的创新特点如下：1)开发和应用新的离散事件监控方法来监控混杂嵌入式系统；2)开发和应用新的方法来验证和监控混杂、分段线性系统；3)开发理论和算法以将这些结果扩展到一类非线性混杂系统；以及4)开发用于混杂系统的新型模型辨识方法和算法。该项目的方法将提高混合嵌入式控制系统处理高复杂性、不可决策性和非线性的能力。