Adaptive dynamic programming for control: A survey and recent advances

D Liu, S Xue, B Zhao, B Luo… - IEEE Transactions on …, 2020‏ - ieeexplore.ieee.org
This article reviews the recent development of adaptive dynamic programming (ADP) with
applications in control. First, its applications in optimal regulation are introduced, and some …

Reinforcement learning in robotic applications: a comprehensive survey

B Singh, R Kumar, VP Singh - Artificial Intelligence Review, 2022‏ - Springer
In recent trends, artificial intelligence (AI) is used for the creation of complex automated
control systems. Still, researchers are trying to make a completely autonomous system that …

Hierarchical sliding-mode surface-based adaptive critic tracking control for nonlinear multiplayer zero-sum games via generalized fuzzy hyperbolic models

H Zhao, G Zong, X Zhao, H Wang… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
This article investigates the hierarchical sliding-mode surface (HSMS)-based adaptive critic
tracking control problem for nonlinear multiplayer zero-sum games (ZSGs). First, a …

Fuzzy approximation-based optimal consensus control for nonlinear multiagent systems via adaptive dynamic programming

H Zhao, H Wang, N Xu, X Zhao, S Sharaf - Neurocomputing, 2023‏ - Elsevier
This paper investigates the fuzzy approximation-based optimal consensus control problem
for nonlinear multiagent systems with unknown perturbations. By constructing local error …

Event-triggered critic learning impedance control of lower limb exoskeleton robots in interactive environments

Y Sun, Z Peng, J Hu, BK Ghosh - Neurocomputing, 2024‏ - Elsevier
In this paper, we present an event-triggered critic learning impedance control algorithm for a
lower limb rehabilitation exoskeleton robot in an interactive environment, where the control …

Deep reinforcement learning for EV charging navigation by coordinating smart grid and intelligent transportation system

T Qian, C Shao, X Wang… - IEEE transactions on …, 2019‏ - ieeexplore.ieee.org
A coordinated operation of smart grid (SG) and intelligent transportation system (ITS)
provides electric vehicle (EV) owners with a myriad of power and transportation network …

Adaptive optimal tracking control of an underactuated surface vessel using actor–critic reinforcement learning

L Chen, SL Dai, C Dong - IEEE Transactions on Neural …, 2022‏ - ieeexplore.ieee.org
In this article, we present an adaptive reinforcement learning optimal tracking control
(RLOTC) algorithm for an underactuated surface vessel subject to modeling uncertainties …

Enhanced coordinated operations of electric power and transportation networks via EV charging services

T Qian, C Shao, X Li, X Wang… - IEEE Transactions on …, 2020‏ - ieeexplore.ieee.org
Electric power and transportation networks become increasingly coupled through electric
vehicles (EV) charging station (EVCS) as the penetration of EVs continues to grow. In this …

Approximate optimal adaptive prescribed performance control for uncertain nonlinear systems with feature information

G Chen, J Dong - IEEE Transactions on Systems, Man, and …, 2024‏ - ieeexplore.ieee.org
This article investigated the performance optimization tracking control problem of strict-
feedback nonlinear systems with feature information. A performance-optimized adaptive …

DRL-based energy-efficient resource allocation frameworks for uplink NOMA systems

X Wang, Y Zhang, R Shen, Y Xu… - IEEE Internet of Things …, 2020‏ - ieeexplore.ieee.org
Nonorthogonal multiple access (NOMA) is one of the promising technologies to meet the
huge access demand and high data-rate requirements of the next-generation networks. In …