CAREER: A New Computational Framework for Control of Complex Systems

职业：复杂系统控制的新计算框架

• 批准号: 1301851
• 负责人: Matthew Peet
• 金额: $ 38.21万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-17 至 2018-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1301851&HistoricalAwards=false
• 关键词: CAREER; New; Computational; Framework; Control

The goal of this Faculty Early Career Development (CAREER) program project is to create reliable algorithms for the control of plasma in a fusion reactor. The approach can be generalized to systems that interact with fluids or structures and/or systems with delay. This project creates a new framework for optimal control of systems described by delayed or partial differential equations (PDEs) based on convex optimization of polynomial variables. A three-step approach is used: First, optimal control of delayed and partial-differential system is expressed as convex optimization of positive operators; Second, positive polynomials are used to parameterize the cone of positive operators; Finally, Sum-of-Squares and semi-definite programming are used to optimize the positive polynomials. The result is a sequence of tractable algorithms for direct control of distributed-parameter systems with decreasing error bounds.Structural or fluid components are modeled by partial differential equations (PDEs) can include plasma in a nuclear fusion reactor, blood flow around an aneurysm, or vibration in an aircraft wing. Sources of delay can include control over a network such as the Internet. Control of systems modeled by PDEs can be challenging due to its complexity. This project considers the control of nuclear fusion plasma - which has yet to experimentally sustain a positive net energy production - the resulting improvement in efficiency may have long-term implications for future worldwide energy production. The project will leverage international collaboration through NSF Office of International Science and Engineering (OISE) Global Venture Fund (GVF) co-funding and integrate with local middle and high school programs to promote energy education as well as building support and public awareness for high-energy magnetic confinement fusion and its role in the national and global energy discussion.

这个教师早期职业发展（职业）计划项目的目标是为融合反应堆中的血浆控制创建可靠的算法。 该方法可以推广到与流体或结构和/或系统延迟相互作用的系统。该项目创建了一个新的框架，以基于多项式变量的凸优化，以延迟或部分微分方程（PDE）描述的系统最佳控制。使用了三步方法：首先，对延迟和部分差异系统的最佳控制表示为正算子的凸优化；其次，阳性多项式用于参数化正算子的锥体。最后，使用方形和半明确编程来优化正多项式。结果是一种可直接控制具有误差界限的分布式参数系统的可拖动算法的序列。结构或流体成分是由部分微分方程（PDE）建模的，可以包括核融合反应器中的等离子体，围绕飞机翼的动脉瘤或振动。延迟的来源可以包括对网络（例如Internet）的控制。由于其复杂性，对由PDE建模的系统的控制可能具有挑战性。 该项目认为对核融合血浆的控制（尚未在实验上维持净能量生产）的控制 - 效率的提高可能会对未来的世界能源生产产生长期影响。 该项目将通过NSF国际科学与工程办公室（OISE）全球风险基金（GVF）共同资助国际合作，并与当地的中学和高中计划集成，以促进能源教育以及建立对高能磁性限制融合及其在国家和全球能源讨论中的作用的支持和公众意识。