Event-triggered reinforcement learning-based safe control for stochastic systems subject to asymmetric input constraints and unknown dynamics.
This paper investigates the safe optimal control (SOC) for input-constrained unknown stochastic systems via adaptive dynamic programming (ADP) and generalized fuzzy hyperbolic model (GFHM). Firstly, a GFHM is employed to approximate the unknown nonlinear terms of the stochastic system, thereby eliminating the need for...