Data-Driven Model Discrimination of Switched Nonlinear Systems With Temporal Logic Inference
This article addresses the problem of data-driven model discrimination for unknown switched systems with unknown linear temporal logic (LTL) specifications, representing tasks, that govern their mode sequences, where only sampled data of the unknown dynamics and tasks are available. To tackle this p...
Main Authors: | Zeyuan Jin, Nasim Baharisangari, Zhe Xu, Sze Zheng Yong |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2023-01-01
|
Series: | IEEE Open Journal of Control Systems |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10271526/ |
Similar Items
-
Model‐based validation of diagnostic software with application in automotive systems
by: Jun Chen, et al.
Published: (2021-06-01) -
FIVER – Robust Verification of Countermeasures against Fault Injections
by: Jan Richter-Brockmann, et al.
Published: (2021-08-01) -
Safety Constraint-Guided Reinforcement Learning with Linear Temporal Logic
by: Ryeonggu Kwon, et al.
Published: (2023-11-01) -
A Survey on Formal Verification and Validation Techniques for Internet of Things
by: Moez Krichen
Published: (2023-07-01) -
A Data Driven Fault Isolation Method Based on Reference Faulty Situations with Application to a Nonlinear Chemical Process
by: Ragot E, et al.
Published: (2022-12-01)