对比了AI驱动与传统控制模型的架构差异及其对系统验证的影响。
Architectural Transformations and Emerging Verification Demands in AI-Enabled Cyber-Physical Systems
- 在Simulink中比较AI与传统控制的架构设计差异
- 揭示了AI引入后系统验证复杂度显著上升
- 适合关注AI-CPS系统可靠性与验证方法的研究者
在网络物理系统（CPS）领域，数字技术与物理世界的实时融合令人瞩目。人工智能（AI）的集成极大地提升了系统的自适应能力，但也引入了新的复杂性，影响着控制系统优化与可靠性。尽管已有进展，但对这一转变如何影响CPS架构、操作复杂性及验证实践的理解仍不充分。本文通过在Simulink中设计并比较基于AI与传统控制的系统架构，探讨其对系统验证的相应影响，旨在填补该研究空白。
原文摘要 · Abstract (English)
In the world of Cyber-Physical Systems (CPS), a captivating real-time fusion occurs where digital technology meets the physical world. This synergy has been significantly transformed by the integration of artificial intelligence (AI), a move that dramatically enhances system adaptability and introduces a layer of complexity that impacts CPS control optimization and reliability. Despite advancements in AI integration, a significant gap remains in understanding how this shift affects CPS architecture, operational complexity, and verification practices. The extended abstract addresses this gap by investigating architectural distinctions between AI-driven and traditional control models designed in Simulink and their respective implications for system verification.
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