CAREER: Toward Real-Time, Constraint-Aware Control of Complex Dynamical Systems: from Theory and Algorithms to Software Tools

职业：实现复杂动力系统的实时、约束感知控制：从理论和算法到软件工具

• 批准号: 2238424
• 负责人: Hamid Ossareh
• 金额: $ 53.58万
• 依托单位: University of Vermont & State Agricultural College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2028-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2238424&HistoricalAwards=false
• 关键词: CAREER; Toward; Real; Time; Constraint

This Faculty Early Career Development (CAREER) grant will fund research that advances knowledge of real-time automatic control with application to complex, safety-critical systems in power, transportation, and manufacturing infrastructure, thereby promoting the progress of science, and advancing the national prosperity. Complex systems are characterized by the coupling of many subsystems, unmodeled components, significant variability, and environmental uncertainty, which prevent effective use of traditional model-based techniques, and render current data-driven approaches computationally intractable. This project addresses these shortcomings by building a new theoretical framework for creating data-based algorithms that are easy to tune by non-experts, real-time feasible, and accompanied by guarantees of safety and performance. A comprehensive plan for pedagogy and outreach aims to integrate the autonomous technology ecosystem in Vermont, establish and strengthen relationships between industry, academia, and government, disseminate research results through sharing of open-source software and accessible video content, and engage with students from underrepresented and underserved communities, including at rural high schools in Vermont.This research aims to develop the foundations for a new data-driven control framework for complex systems, which decouples the problems of tracking and constraint management through a marriage of the Internal Model Control and Reference Governor model-based design techniques with the Behavioral Systems Theory data-driven approach. By inheriting many desirable properties of the model-based approaches, such as robust stability, constraint enforcement, and finite-time convergence to constraint-admissible setpoints, this framework overcomes the limitations of data-driven approaches within a modular structure that simplifies analysis and design, and allows for easily tunable, computationally tractable algorithms. To this end, the project will investigate the system-theoretic underpinnings of the new control framework, characterize its properties and fundamental limitations, and develop generalizations to nonlinear, time-varying, and unstable systems. Informed by collaboration with Beta Technologies and the Vermont Electric Power Company, VELCO, the control framework will be validated on an electric motor experiment, a quadrotor swarm transporting a complex payload, and a hardware-in-the-loop simulation of a power system with significant penetration of distributed energy resources. This project is jointly funded by the Dynamics, Control and Systems Diagnostics program and the Established Program to Stimulate Competitive Research (EPSCoR).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该教师早期职业发展 (CAREER) 赠款将资助研究，以推进实时自动控制知识的研究，并将其应用于电力、交通和制造基础设施中的复杂、安全关键系统，从而促进科学进步，并推动国家发展。繁荣。复杂系统的特点是许多子系统的耦合、未建模的组件、显着的可变性和环境不确定性，这阻碍了传统基于模型的技术的有效使用，并使当前的数据驱动方法在计算上难以处理。该项目通过构建一个新的理论框架来解决这些缺点，该框架用于创建基于数据的算法，该算法易于非专家调整、实时可行，并具有安全性和性能保证。一项全面的教学和推广计划旨在整合佛蒙特州的自主技术生态系统，建立和加强行业、学术界和政府之间的关系，通过共享开源软件和可访问的视频内容传播研究成果，并与来自弱势群体的学生互动这项研究旨在为复杂系统的新数据驱动控制框架奠定基础，该框架通过内部模型控制和约束管理的结合来解耦跟踪和约束管理问题。参考基于调控器模型的设计技术和行为系统理论数据驱动方法。通过继承基于模型的方法的许多理想属性，例如鲁棒稳定性、约束执行和有限时间收敛到约束允许的设定点，该框架克服了模块化结构中数据驱动方法的局限性，从而简化了分析和设计，并允许轻松调整、计算上易于处理的算法。为此，该项目将研究新控制框架的系统理论基础，描述其属性和基本局限性，并对非线性、时变和不稳定系统进行推广。通过与 Beta Technologies 和佛蒙特州电力公司 VELCO 的合作，该控制框架将在电动机实验、运输复杂有效载荷的四旋翼飞行器群以及电力系统的硬件在环仿真中进行验证分布式能源的显着渗透。该项目由动力学、控制和系统诊断计划以及刺激竞争研究既定计划 (EPSCoR) 共同资助。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查进行评估，被认为值得支持标准。