Cyber-Physical Networks: Foundations, Correct-by-Construction Control Design, and Applications

信息物理网络：基础、构造修正控制设计和应用

• 批准号: RGPIN-2016-04139
• 负责人: Liu, Jun
• 金额: $ 2.62万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=708231
• 关键词: Cyber; Physical; Networks; Foundations; Correct

Engineered systems of the future will feature increasingly tight interactions between their computational and physical components. Systems of this type are referred to as cyber-physical systems (CPS) and have attracted considerable attention worldwide for their potential impact on a variety of industrial sectors. While most targeted CPS applications are evidently of safety-critical nature, e.g., next-generation transportation systems, power grids, and medical devices, how to affordably build and efficiently certify these systems as safe, reliable, and high performance remains one of the grand challenges of CPS research. Current practice often heavily relies on ex-post verification to deliver assurance, which typically involves extensive testing and simulations, usually at a significant cost, and may rapidly become intractable for complex designs. Motivated by the above challenge, the proposed research program aims to contribute to a paradigm shift in the design of such systems, from the traditional "design and verify" approach to a "specify and synthesize" approach; that is, start with a formal, system-level specification (e.g. that can be described by temporal logics) and seek to design systems that satisfy desired properties encoded in the specification by construction (known as correct-by-construction design). The proposed research lies at the broad interface of control engineering, computer science, and applied mathematics. The long-term aim (5-10 years) is to fundamentally advance the understanding of and provide new design paradigms for CPS. The short-term objectives (1-5 years) are to: (1) lay a theoretical foundation for the modelling and analysis of networked CPS via the building blocks of interconnected hybrid systems; (2) develop enabling theories and scalable tools for the correct-by-construction control synthesis for networked CPS from rigorous specifications; and (3) demonstrate the correct-by-construction design methodology in networked autonomous robotic vehicles and electric power systems via physical and numerical experiments. The program for achieving the above objectives consists of three technical themes and provides plenty of scope for HQP training at various levels of research: 1) Modelling and analysis of hybrid dynamical networks in CPS (PhD 1); 2) Correct-by-construction control synthesis for networked CPS (PhD 2); 3) Domain-specific CPS applications in robotics (Master 1, Undergraduates) and power systems (Master 2, Undergraduates). The integration between analytical, computational, and experimental methods across the above technical themes will bring significant added value to the proposed program and HQP training plan. The inter-disciplinary challenges present in this program will provide opportunities to cross and push the boundaries of four technical areas of hybrid systems, formal methods, robotics, and power systems.

未来的工程系统将以其计算和物理组件之间越来越紧密的相互作用为特征。这种类型的系统被称为网络物理系统（CPS），由于其对各种工业部门的潜在影响而在全世界引起了相当大的关注。虽然大多数目标CPS应用显然具有安全关键性，例如，下一代交通系统、电网和医疗设备，如何负担得起构建和有效地认证这些系统安全、可靠和高性能仍然是CPS研究的重大挑战之一。目前的做法往往严重依赖于事后验证来提供保证，这通常涉及大量的测试和模拟，通常成本很高，并且对于复杂的设计可能很快变得难以处理。 受上述挑战的激励，拟议的研究计划旨在促进这种系统设计的范式转变，从传统的“设计和验证”方法到“指定和综合”方法;也就是说，系统级规格（例如，可以由时间逻辑描述的），并寻求设计满足通过构造在规范中编码的期望属性的系统（称为正确的建筑设计）。 拟议的研究在于控制工程，计算机科学和应用数学的广泛接口。长期目标（5-10年）是从根本上推进对CPS的理解，并为CPS提供新的设计范例。短期目标（1-5年）是：（1）通过互联混合系统的构建模块，为网络化CPS的建模和分析奠定理论基础;（2）根据严格的规范，为网络化CPS的结构正确控制综合开发使能理论和可扩展工具;以及（3）通过物理和数值实验证明了网络化自主机器人车辆和电力系统中的正确构造设计方法。 实现上述目标的计划包括三个技术主题，并提供了大量的范围，为HQP培训在不同层次的研究：1）建模和分析的混合动力网络在CPS（博士1）; 2）正确的结构控制综合网络CPS（博士2）; 3）机器人（硕士1，本科生）和电力系统（硕士2，本科生）领域特定的CPS应用。上述技术主题中分析、计算和实验方法的整合将为拟议的计划和HQP培训计划带来显著的附加值。该计划中存在的跨学科挑战将提供跨越和推动混合动力系统，正式方法，机器人和电力系统四个技术领域边界的机会。