Hybrid dynamical systems logic and its refinements

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Science of Computer Programming Pub Date : 2024-07-25 DOI:10.1016/j.scico.2024.103179
André Platzer
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引用次数: 0

Abstract

Hybrid dynamical systems describe the mixed discrete dynamics and continuous dynamics of cyber-physical systems such as aircraft, cars, trains, and robots. To justify correctness properties of the safety-critical control algorithms for their physical models, differential dynamic logic (

) provides deductive specification and verification techniques implemented in the theorem prover
. The logic
is useful for proving, e.g., that all runs of a hybrid dynamical system α satisfy safety property φ (i.e.,
), or that there is a run of the hybrid dynamical system α ultimately reaching the desired goal φ (i.e.,
). Logical combinations of
's operators naturally represent safety, liveness, stability and other properties. Variations of
serve additional purposes. Differential refinement logic (
) adds an operator αβ expressing that hybrid system α refines hybrid system β, which is useful, e.g., for relating concrete system implementations α to their abstract verification models β. Just like
,
is a logic closed under all operators, which opens up systematic ways of simultaneously relating systems and their properties, of reducing system properties to system relations or, vice versa, reducing system relations to system properties. A second variant of
, differential game logic (
), adds the ability of referring to winning strategies of players in hybrid games, which is useful for establishing correctness properties where the actions of different agents may interfere either because they literally compete with one another or because they may interact accidentally. In the theorem prover
,
and its variations have been used for verifying ground robot obstacle avoidance, the Federal Aviation Administration's Next-Generation Airborne Collision Avoidance System ACAS X, and the Federal Railroad Administration's train control model.

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混合动力系统逻辑及其完善
混合动力系统描述了飞机、汽车、火车和机器人等网络物理系统的混合离散动力和连续动力。为了证明其物理模型的安全关键控制算法的正确性,微分动态逻辑()提供了在定理证明器中实现的演绎规范和验证技术。该逻辑可用于证明混合动力系统 α 的所有运行都满足安全属性 φ (即),或证明混合动力系统 α 有一个运行最终达到预期目标 φ (即)。运算符'的逻辑组合自然代表了安全性、有效性、稳定性和其他属性。的变体还有其他用途。微分细化逻辑()增加了一个运算符 α≤β 表示混合系统 α 细化混合系统 β,这对于将具体的系统实现 α 与它们的抽象验证模型 β 联系起来非常有用,就像Ⅳ是一个在所有运算符下都封闭的逻辑一样,它开辟了同时联系系统及其属性、将系统属性还原为系统关系或反之将系统关系还原为系统属性的系统化方法。微分博弈逻辑()的第二种变体增加了在混合博弈中参考博弈者获胜策略的能力,这对于建立正确性属性非常有用,因为在混合博弈中,不同代理的行动可能会相互干扰,这可能是因为它们在字面上相互竞争,也可能是因为它们可能意外地相互作用。在定理证明器中,及其变体已被用于验证地面机器人避障、美国联邦航空管理局的下一代空中防撞系统 ACAS X 和美国联邦铁路管理局的列车控制模型。
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来源期刊
Science of Computer Programming
Science of Computer Programming 工程技术-计算机:软件工程
CiteScore
3.80
自引率
0.00%
发文量
76
审稿时长
67 days
期刊介绍: Science of Computer Programming is dedicated to the distribution of research results in the areas of software systems development, use and maintenance, including the software aspects of hardware design. The journal has a wide scope ranging from the many facets of methodological foundations to the details of technical issues andthe aspects of industrial practice. The subjects of interest to SCP cover the entire spectrum of methods for the entire life cycle of software systems, including • Requirements, specification, design, validation, verification, coding, testing, maintenance, metrics and renovation of software; • Design, implementation and evaluation of programming languages; • Programming environments, development tools, visualisation and animation; • Management of the development process; • Human factors in software, software for social interaction, software for social computing; • Cyber physical systems, and software for the interaction between the physical and the machine; • Software aspects of infrastructure services, system administration, and network management.
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