Causal Signal Temporal Logic for the Environmental Control and Life Support System’s Fault Analysis and Explanation
Open Access
- 20 February 2023
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Access
- Vol. 11, 26471-26482
Abstract
Modern cyber-physical systems would often fall victim to unanticipated anomalies. Humans are still required in many operations to troubleshoot and respond to such anomalies, such those in future deep space habitats. To maximize the effectiveness and efficiency of the anomaly response process, the information provided by anomaly response technologies to their human operators must be epistemically accessible or explainable. This paper offers a first step towards developing explainable anomaly response systems. It proposes a logic, Causal Signal Temporal Logic (CaSTL), which can formally describe cause-effect relationships pertaining to fault explanation. Moreover, it develops an algorithm to infer a CaSTL formula that explains why a fault has happened in a system, given the model of the system and an observation about the fault. The effectiveness of the proposed algorithm is demonstrated with a simulated Environmental Control and Life Support System (ECLSS).Keywords
Funding Information
- National Aeronautics and Space Administration’s Space Technology Research Grants Program (80NSSC19K1052)
This publication has 35 references indexed in Scilit:
- Fault detection and explanation through big data analysis on sensor streamsExpert Systems with Applications, 2017
- An improved Cyber-Physical Systems architecture for Industry 4.0 smart factories2017
- Model-Free Fault Detection and Isolation in Large-Scale Cyber-Physical SystemsIEEE Transactions on Emerging Topics in Computational Intelligence, 2016
- Temporal Logics for Learning and Detection of Anomalous BehaviorIEEE Transactions on Automatic Control, 2016
- Model predictive control with signal temporal logic specifications2014
- On Signal Temporal LogicLecture Notes in Computer Science, 2013
- Robust Satisfaction of Temporal Logic over Real-Valued Signals2010
- Causality2009
- GAUSSIAN PROCESSES FOR MACHINE LEARNINGInternational Journal of Neural Systems, 2004
- Probabilistic Causality1991