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
Enhancing Vehicle Lateral Stability: A DDPG-Based Active Anti-Roll Bar Control Strategy
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3480116
Abstract: In recent years, Active Anti-Roll Bars (AARB) have become an important research direction aimed at improving vehicle comfort and lateral stability. Previous studies have indicated that asymmetric issues can occur when using reinforcement learning (RL)… read more here.
Keywords: control strategy; vehicle; active anti; ddpg ... 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
Blind Channel Estimation and Symbol Recovery Based on DDPG Algorithm
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Communications Letters"
DOI: 10.1109/lcomm.2025.3610628
Abstract: Blind channel estimation (BCE) plays a critical role in wireless systems, aiming to recover channel information without relying on pilot signals. To enable accurate joint recovery of transmitted symbols and estimation of multipath channels, this… read more here.
Keywords: algorithm; recovery; estimation; blind channel ... 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
An Energy Management Strategy Based on DDPG With Improved Exploration for Battery/Supercapacitor Hybrid Electric Vehicle
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2023.3327105
Abstract: Given that transportation contributes to 23% of global energy-related greenhouse gas emissions, the electrification of the transport sector is an inevitable trend. This paper presents a hybrid energy management method that utilizes the Deep Deterministic… read more here.
Keywords: battery; energy; exploration; ddpg ... See more keywords
On Adaptive Edge Microservice Placement: A Reinforcement Learning Approach Endowed With Graph Comprehension
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Mobile Computing"
DOI: 10.1109/tmc.2024.3396510
Abstract: Microservice (MS) structures a service application as a collection of independently deployable service modules, making it particularly suitable for delivering complex applications in distributed computing systems. This article investigates MS architecture over Mobile Edge Computing… read more here.
Keywords: ddpg; microservice; gnn; edgems placement ... See more keywords
Deep Reinforcement Learning Lane-Changing Decision Algorithm for Intelligent Vehicles Combining LSTM Trajectory Prediction
Sign Up to like & getrecommendations! Published in 2024 at "World Electric Vehicle Journal"
DOI: 10.3390/wevj15040173
Abstract: Intelligent decisions for autonomous lane-changing in vehicles have consistently been a focal point of research in the industry. Traditional lane-changing algorithms, which rely on predefined rules, are ill-suited for the complexities and variabilities of real-world… read more here.
Keywords: lstm ddpg; lane changing; prediction; ddpg ... See more keywords