A framework reformulates safety-constrained infinite-horizon optimal control as an unconstrained problem on an extended state space using barrier-Lyapunov functions, auxiliary variables, adaptive excitation, and online critic learning for disturbed high-relative-degree systems.
A safety aware model-based re- inforcement learning framework for systems with uncer- tainties
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.SY 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Synthesizing Safety in Infinite-Horizon Optimal Control for Disturbed High-Relative-Degree Systems via Barrier-Regulating Auxiliary Variables
A framework reformulates safety-constrained infinite-horizon optimal control as an unconstrained problem on an extended state space using barrier-Lyapunov functions, auxiliary variables, adaptive excitation, and online critic learning for disturbed high-relative-degree systems.