Neural network co-design of output-feedback CBF, observer, and controller for partially observed continuous-time systems with input constraints, using augmented-state barrier conditions and a validity condition for safety guarantees beyond training data.
Formal verification of unknown discrete-and continuous-time systems: A data-driven approach
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.SY 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Neural Network-based Co-design of Output-Feedback Control Barrier Function and Observer with Input Constraints
Neural network co-design of output-feedback CBF, observer, and controller for partially observed continuous-time systems with input constraints, using augmented-state barrier conditions and a validity condition for safety guarantees beyond training data.