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.
Safe exploration in model- based reinforcement learning using control barrier func- tions
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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.