This paper reviews the current state of the art on reinforcement learning (RL)-based
feedback control solutions to optimal regulation and tracking of single and multiagent …

Abstract Space debris is one of the most urgent issues of modern astronautics, which
solution requires a systematic and coordinated efforts of international community. Several …

This article presents a novel efficient experience-replay-based adaptive dynamic
programming (ADP) for the optimal control problem of a class of nonlinear dynamical …

Reinforcement learning (RL) has roots in dynamic programming and it is called
adaptive/approximate dynamic programming (ADP) within the control community. This paper …

This article presents a model-free-policy iteration (-PI) for the discrete-time linear quadratic
regulation (LQR) problem. To solve the algebraic Riccati equation arising from solving the …

This article investigates a neural network (NN)‐based control problem for unknown discrete‐
time nonlinear systems with a denial‐of‐service (DoS) attack and an adaptive event …

The fault-tolerant control problem of a hydraulic servo actuator in the presence of actuator
faults is studied utilizing adaptive dynamic programming. This task is challenging because of …

This article presents a learning‐based barrier certified method to learn safe optimal
controllers that guarantee operation of safety‐critical systems within their safe regions while …

This article considers the robust optimal control problem for a class of nonlinear systems in
the presence of unmodeled dynamics. An adaptive optimal controller is designed using the …

Hydraulic servo actuators (HSAs) are often used in the industry in tasks that request great
power, high accuracy and dynamic motion. It is well known that an HSA is a highly complex …