Integrated Communication, Sensing, Computing, and Control for Industrial Power Protection Systems: Analysis and Performance Optimization | Zendy

Tongshan Liu | Zendy; Jiangtao Zhang | Zendy; You Liu | Zendy; Chunyou Zhuang | Zendy; Hao Li | Zendy; Yuanyuan Chen | Zendy

Open Access

Integrated Communication, Sensing, Computing, and Control for Industrial Power Protection Systems: Analysis and Performance Optimization

Author(s) -

Tongshan Liu,

Jiangtao Zhang,

You Liu,

Chunyou Zhuang,

Hao Li,

Yuanyuan Chen

Publication year - 2025

Publication title -

ieee access

Language(s) - English

Resource type - Magazines

SCImago Journal Rank - 0.587

H-Index - 127

eISSN - 2169-3536

DOI - 10.1109/access.2025.3595277

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

With the continuous advancement of industrial automation technology, industrial power security systems are playing an increasingly important role in ensuring production stability and improving efficiency. This paper studies an industrial power security system that integrates sensing, communication, computation, and control (ISCC), focusing on the performance optimization issues related to latency and reliability. Addressing the trade-offs between latency and reliability across the four components of sensing, communication, computation, and control, and assuming no errors in sensing, closed-form expressions for the maximum latency of the communication-sensing-computation-control system and the maximum packet loss probability of communication are derived. By optimizing the optimal control law and the system’s uplink and downlink bandwidth under constraints of communication rate, maximum available bandwidth, and power, the control cost of the system is minimized. To further enhance system performance, this paper proposes a joint optimization method aimed at simultaneously optimizing the control law and uplink-downlink bandwidth allocation to minimize the system’s control cost.

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