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

This paper addresses the finite-time event-triggered control problem for nonlinear semi-
Markovian switching cyber-physical systems (S-MSCPSs) under false data injection (FDI) …

This paper addresses the sliding-mode surface-based adaptive optimal nonzero-sum
games control problem for continuous-time nonlinear systems with input constraints. By …

This article studies the hierarchical sliding-mode surface (HSMS)-based adaptive optimal
control problem for a class of switched continuous-time (CT) nonlinear systems with …

In this paper, an event-triggered control scheme with periodic characteristic is developed for
nonlinear discrete-time systems under an actor–critic architecture of reinforcement learning …

This paper investigates the fuzzy approximation-based optimal consensus control problem
for nonlinear multiagent systems with unknown perturbations. By constructing local error …

This paper studies the sliding-mode surface (SMS)-based approximate optimal control issue
for a class of nonlinear multiplayer Stackelberg-Nash games (MSNGs). First, considering …

This paper addresses the adaptive optimal containment control issue for non-affine
nonlinear multi-agent systems in the presence of periodic disturbances. To deal with the …

This paper presents an event-triggered adaptive dynamic programming (ETADP) algorithm
to study the optimal decentralized control issue of interconnected nonlinear systems subject …

In this work, based on the adaptive critic learning algorithms and fuzzy logic systems, the
decentralized optimal control problem for interconnected nonlinear systems with unmodeled …