A new adaptive controller based on distributed deep reinforcement learning for PEMFC air supply system
Sign Up to like & getrecommendations! Published in 2021 at "Energy Reports"
DOI: 10.1016/j.egyr.2021.02.043
Abstract: Abstract To better control the PEMFC air flow, this paper introduces a distributed deep reinforcement learning-based adaptive proportional integral (PI) controller for controlling air flow in a proton exchange membrane fuel cell (PEMFC). In this… read more here.
Keywords: pemfc air; distributed deep; controller; exploration ... See more keywords
Autonomous Platoon Control With Integrated Deep Reinforcement Learning and Dynamic Programming
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3222128
Abstract: Autonomous vehicles in a platoon determine the control inputs based on the system state information collected and shared by the Internet of Things (IoT) devices. Deep reinforcement learning (DRL) is regarded as a potential method… read more here.
Keywords: dynamic programming; autonomous platoon; reinforcement learning; deep reinforcement ... See more keywords
Hybrid Reinforcement Learning for STAR-RISs: A Coupled Phase-Shift Model Based Beamformer
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal on Selected Areas in Communications"
DOI: 10.1109/jsac.2022.3192053
Abstract: A simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted multi-user downlink multiple-input single-output (MISO) communication system is investigated. In contrast to the existing ideal STAR-RIS model assuming an independent transmission and reflection phase-shift control,… read more here.
Keywords: phase shift; phase; ddpg; coupled phase ... See more keywords
Distributed Beamforming Techniques for Cell-Free Wireless Networks Using Deep Reinforcement Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Cognitive Communications and Networking"
DOI: 10.1109/tccn.2022.3165810
Abstract: In a cell-free network, a large number of mobile devices are served simultaneously by several base stations (BSs)/access points(APs) using the same time/frequency resources. However, this creates high signal processing demands (e.g., for beamforming) at… read more here.
Keywords: reinforcement learning; cell free; deep reinforcement; ddpg ... See more keywords
DDPG-Based Joint Time and Energy Management in Ambient Backscatter-Assisted Hybrid Underlay CRNs
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Communications"
DOI: 10.1109/tcomm.2022.3221422
Abstract: Ambient backscatter (AB) communications and radio frequency (RF)-powered cognitive radio networks (CRNs) address the concerns of energy and spectrum scarcities from different perspectives, and the integration of them has potential benefits for throughput. Motivated by… read more here.
Keywords: assisted hybrid; crn; hybrid underlay; energy ... See more keywords
Asynchronous Episodic Deep Deterministic Policy Gradient: Toward Continuous Control in Computationally Complex Environments
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Cybernetics"
DOI: 10.1109/tcyb.2019.2939174
Abstract: Deep deterministic policy gradient (DDPG) has been proved to be a successful reinforcement learning (RL) algorithm for continuous control tasks. However, DDPG still suffers from data insufficiency and training inefficiency, especially, in computationally complex environments.… read more here.
Keywords: computationally complex; deep deterministic; control; deterministic policy ... See more keywords