Collaborative Research: CPS: Frontier: Computation-Aware Algorithmic Design for Cyber-Physical Systems

合作研究：CPS：前沿：网络物理系统的计算感知算法设计

• 批准号: 2111688
• 负责人: Ricardo Sanfelice
• 金额: $ 575.85万
• 依托单位: University of California-Santa Cruz
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2111688&HistoricalAwards=false
• 关键词: Collaborative; Research; CPS; Frontier; Computation; Collaborative; Research; CPS; Frontier; Computation

This project explores a new vision of cyber-physical systems (CPSs) in which computing power and control methods are jointly considered. The approach is carried out through exploration of new theories for the modeling, analysis, and design of CPSs that operate under computational constraints. The tight coupling between computation, communication, and control pervades the design and application of CPSs. Due to the complexity of such systems, advanced design procedures that cope with the variability and uncertainty introduced by computing resources are mandatory, though the design choices are across many disciplines, which may result in over-design of a system. The project will have significant impact through the reduction in design and development time for complex cyber physical systems including ground, air, and maritime vehicles.The proposed innovative research plan will advance the knowledge on modeling, analysis, and design of high-performance CPSs operating under computational constraints. By combining key expertise from hardware architecture, real-time systems, nonlinear control, hybrid systems, and optimization algorithms, the developed CPSs will execute algorithms that adapt to the platforms they operate in and to the environment they are deployed on. Additionally, the new platforms to emerge from this project may adapt to the algorithms, through reallocation of resources and self-adaptation/augmentation at runtime, by learning the main features of the platform (e.g., execution time, memory footprint, and power consumption) and of the physics (e.g., dynamics, actuation, sensing). This project will also generate tools to automatically design, synthesize, and implement feedback control algorithms that are compatible with both the physics and the computing platforms in the CPSs. Tools will be validated experimentally in intelligent transportation applications, including real-world ground, aerial, and marine autonomous vehicles, both in-house and in collaboration with our academic and industrial partners.The broader impacts of this project stem from the potential to enable a new generation of transportation systems that improve the reliability and security of autonomous systems. The research in this project significantly addresses the growing carbon footprint challenge through efficiencies in computational CPS infrastructure, optimization of routes, and by increasing the utilization of autonomous systems. Industry partners may deploy enhanced safety and performance innovations on legacy vehicles, diversify hardware applications, and expand future technologies. Additional efforts in mentoring and undergraduate research are focused on Broadening Participation in Computing, with the goal to empower a new generation of researchers who are passionate to have impact on a societal scale.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.

该项目探讨了共同考虑计算能力和控制方法的网络物理系统（CPSS）的新愿景。该方法是通过探索在计算约束下运行的CPS建模，分析和设计的新理论进行的。计算，通信和控制之间的紧密耦合遍及CPS的设计和应用。由于此类系统的复杂性，因此必须应对计算资源引入的可变性和不确定性的高级设计程序是必须的，尽管设计选择是在许多学科中，这可能会导致系统过度设计。 该项目将通过减少设计和开发时间的复杂网络物理系统（包括地面，空气和海上车辆）的设计产生重大影响。拟议的创新研究计划将提高有关在计算约束下运行的高性能CPSS建模，分析和设计的知识。通过结合硬件体系结构，实时系统，非线性控制，混合系统和优化算法的关键专业知识，开发的CPSS将执行适应其在其中和部署其环境中运行的平台的算法。此外，通过学习平台的主要特征（例如，执行时间，内存足迹和功耗）以及物理学（例如，动态，动态，动态，动态，传感），通过学习资源和自我适应/增强时，可以通过重新分配资源和自动适应/增强来适应算法的新平台。 该项目还将生成工具，以自动设计，合成和实施与CPSS中物理和计算平台兼容的反馈控制算法。工具将在智能运输应用中进行实验验证，包括内部和与我们的学术和工业合作伙伴合作的现实世界，空中和海洋自动驾驶汽车。该项目的更广泛影响源于启用新一代运输系统，从而提高自动系统的可靠性和安全性。该项目中的研究通过计算CPS基础架构的效率，路线的优化以及增加自主系统的利用来显着解决碳足迹挑战的日益增长的挑战。行业合作伙伴可以在旧车上部署增强的安全性和性能创新，使硬件应用多样化并扩展未来的技术。在指导和本科研究方面的额外努力集中在扩大计算中的参与，目的是赋予新一代的研究人员，他们热衷于对社会规模产生影响。这项奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评估来通过评估来获得支持的。