课题基金 / 基金详情

Dynamic Modeling, Analysis, and Synthesis of Embedded Hybrid Systems

Dynamic Modeling, Analysis, and Synthesis of Embedded Hybrid Systems
嵌入式混合系统的动态建模、分析和综合
批准号:
0208799
负责人:
Gautam Biswas
金额:
$27.53万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2002
资助国家:
美国
项目状态:
已结题
起止时间:
2002-08-01 至 2005-07-31

项目摘要

项目成果

Gautam Biswas的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
Biswas, GautamCCR-0208799Embedded systems, which include software components integrated into physical processes, are per-vading all aspects of our daily lives from home appliances to safety-critical systems, such as aircraft and nuclear plants. The widespread use necessitates the development of new engineering tech-niques that can ensure their timely and assured development, accurate monitoring during operation, and robust control, to ensure safety and reliability. This project develops an integrated model-based approach to embedded system development that includes the plant, its environment, and the embed-ded computing system. The models provide a common framework for design and run-time analyses of system stability, liveliness, safety, security, and real-time supervisory control. Models can also form the basis for generating the hardware and software components of the embedded systems, and de-fining their run-time configurations. This generative aspect of modeling is a very relevant and distin-guishing property of the model-based development process. Further, the ability to analyze system behavior at run-time forms the basis for methodologies designed to accommodate deviations caused by disturbances and unexpected changes in the environment. The goal is to ensure that the system and its surroundings are not harmed when aberrant situations occur.The project will develop technologies for run-time analysis of embedded systems that alleviate some of the complexities of modeling and analysis of systems with large mode spaces. Specifically, effec-tive methodologies that address run-time dynamic analysis issues are addressed. This includes three primary tasks:Developing a new concept called the dynamic hybrid automaton (DHA) for embedded sys-tems models with large mode spaces. A DHA is simply a hybrid automaton, which can be constructed incrementally, on-the-fly, at run-time, as system behavior evolves. It is based on formal compositional modeling techniques in the hybrid automata framework that ensure model construction grows linearly (as opposed to exponentially) as a function of the number of switching elements in the hybrid model. Tracking system behavior using hybrid observers developed from the hybrid automata mod-els. This involves techniques for updating the models of the observer on-line when a mode change is detected while tracking the plant behavior. Research challenges focus on model and tracking procedures that minimize mistracking at mode transition boundaries, and devel-oping code generation systems that allow for incremental recalculation of the observer mod-els while satisfying hard time bounds on the generation process, and Synthesizing supervisory controllers on-line in response to mode changes, some of which may be attributed to disturbances and unexpected changes in the environment. A new con-cept, the Active Controller Model (ACM), is proposed. The ACM is a dynamic data structure that explicitly represents the currently active supervisory controller (SVC), together with its generator and actuator. The SVC can be implemented as a generic procedure that uses the ACM as its "knowledge base" to compute what control actions to take. When the plant model changes, the ACM is updated to address the new situation. This will involve a number of in-novative research tasks, such as developing an expressive language to describe control ob-jectives, definition and incremental update procedures for the ACM models, and "anytime" re-source-bound algorithms for synthesizing supervisory controller code on-line. Robust super-visory controllers will extend the concept of adaptive control into the hybrid-systems domain, and adjust to configuration changes in the plant and environment. The success of all three components of this project is very heavily dependent on handling computa-tional complexity issues in incremental model generation, code generation for the hybrid observer, and on-line supervisory controller synthesis based on desired objectives for the plant. Therefore, complexity studies of the synthesis and code generation algorithms is an important component of the project. The goals are ambitious, but the success of these methods will offer new flexibility in embed-ded applications while addressing issues of reliability and safety during run-time operation.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
EAGER: Co-Designing a Cognitive Teaching Assistant to Support Evidence-Based Instruction in Open-Ended Learning Environments
  • 批准号:
    2327708
  • 项目类别:
    Standard Grant
  • 资助金额:
    $30.0万
  • 财政年份:
    2023
  • 负责人:
    Gautam Biswas
  • 依托单位:
Collaborative Research: Computational Modeling for Integrating Science and Engineering Design: Model Construction, Manipulation, and Exploration
  • 批准号:
    2055597
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $51.09万
  • 财政年份:
    2021
  • 负责人:
    Gautam Biswas
  • 依托单位:
Analyzing and Supporting Students' Learning Behaviors in Computational STEM Learning Environments
  • 批准号:
    2017000
  • 项目类别:
    Standard Grant
  • 资助金额:
    $74.92万
  • 财政年份:
    2020
  • 负责人:
    Gautam Biswas
  • 依托单位:
Collaborative Research: An Interdisciplinary Approach to Prepare Undergraduates for Data Science Using Real-World Data from High Frequency Monitoring Systems
  • 批准号:
    1915487
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $63.14万
  • 财政年份:
    2019
  • 负责人:
    Gautam Biswas
  • 依托单位:
国内基金
海外基金
Galaxy Analytical Modeling Evolution (GAME) and cosmological hydrodynamic simulations.
  • 批准号:
  • 项目类别:
    省市级项目
  • 资助金额:
    10.0万元
  • 批准年份:
    2025
  • 负责人:
    Antonios Katsianis
  • 依托单位: