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

该项目探索了网络物理系统（cps）的新愿景，其中计算能力和控制方法被联合考虑。该方法是通过探索在计算约束下运行的cps的建模、分析和设计的新理论来实现的。计算、通信和控制之间的紧密耦合贯穿于cps的设计和应用中。由于这类系统的复杂性，处理由计算资源引入的可变性和不确定性的高级设计程序是强制性的，尽管设计选择跨越许多学科，这可能导致系统的过度设计。该项目将通过减少复杂网络物理系统（包括地面、空中和海上车辆）的设计和开发时间产生重大影响。提出的创新研究计划将推进在计算约束下运行的高性能cps的建模、分析和设计方面的知识。通过结合硬件架构、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cps将执行适应其运行平台和部署环境的算法。此外，从这个项目中出现的新平台可以通过重新分配资源和在运行时自适应/增强来适应算法，通过学习平台的主要特性（例如，执行时间，内存占用和功耗）和物理特性（例如，动力学，驱动，传感）。该项目还将生成工具来自动设计、合成和实现与cps中的物理和计算平台兼容的反馈控制算法。这些工具将在智能交通应用中进行实验验证，包括现实世界的地面、空中和海上自动驾驶汽车，无论是内部还是与我们的学术和工业合作伙伴合作。该项目的更广泛影响源于新一代交通系统的潜力，这些系统可以提高自动驾驶系统的可靠性和安全性。该项目的研究通过提高计算CPS基础设施的效率、优化路线和提高自主系统的利用率，显著解决了日益增长的碳足迹挑战。行业合作伙伴可以在传统车辆上部署增强的安全性和性能创新，使硬件应用多样化，并扩展未来技术。在指导和本科生研究方面的额外努力侧重于扩大对计算机的参与，其目标是使新一代的研究人员能够对社会规模产生影响。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.