Enabling Online Fault Prediction in Adaptive Control: A Model Checker and Controller Co-Designed CPS Solution

Yao Chen, Xueli Fan, Qixin Wang*, Nan Guan, Shuai Li, Zili Shao

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

Abstract

By combining cyber subsystem of model checker with physical subsystem of control, online model checking of control systems can serve as a runtime fault prediction method to increase control systems safety. Online model checking of adaptive control systems, however, incurs more challenging time costs, due to the uncertainty caused by unknown control system parameter values. In this paper, we first propose a safety-oriented adaptive controller (SOAC) to replace the classic adaptive controller. This cuts online model checking time cost from \Omega(Jd^{n+p-1}) to O(Jd^{n-1}), where J and d are scalable configuration parameters, raising which refines numerical computation granularity; n is the dimension of the physical state; and p+1 is the dimension of control system parameters with unknown values. We further propose a specialized model checker for SOAC, and prove under mild conditions, the proposed model checker can further cut model checking time cost to O(J).

Original languageEnglish
Title of host publication2024 IEEE 14th International Symposium on Industrial Embedded Systems, SIES 2024
PublisherIEEE Institute of Electrical and Electronic Engineers
Pages85-92
Number of pages8
ISBN (Electronic)9798350388633
DOIs
Publication statusPublished - 2024
MoE publication typeA4 Article in a conference publication
Event14th IEEE International Symposium on Industrial Embedded Systems, SIES 2024 - Chengdu, China
Duration: 23 Oct 202425 Oct 2024

Conference

Conference14th IEEE International Symposium on Industrial Embedded Systems, SIES 2024
Country/TerritoryChina
CityChengdu
Period23/10/2425/10/24

Keywords

  • adaptive control
  • CPS
  • reachability

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