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Journal ArticleDOI

Distributed deep reinforcement learning-based coordination performance optimization method for proton exchange membrane fuel cell system

Jiawen Li, +2 more
- 01 Mar 2022 - 
- Vol. 50, pp 101814-101814
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TLDR
In this paper , a metaverse-based multiagent double delay deep deterministic policy gradient (MET-MADDPG) algorithm is proposed to achieve coordinated control of multiple operating variables and thus improve the stability, performance, and efficiency of the PEMFC power system.
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This article is published in Sustainable Energy Technologies and Assessments.The article was published on 2022-03-01. It has received 6 citations till now. The article focuses on the topics: Reinforcement learning & Computer science.

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Citations
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Journal ArticleDOI

Optimization of geometric parameters of ejector for fuel cell system based on multi-objective optimization method

TL;DR: In this paper , a multi-objective orthogonal experiment is employed to optimize the geometric parameters of the ejector, including the nozzle exit diameter, nozzle exit position, mixing chamber length, and mixing chamber diameter.
Journal ArticleDOI

A State-of-the-Art Survey on Various Domains of Multi-Agent Systems and Machine Learning

TL;DR: In this paper , a broad review of the current developments in the field of MASs combined with machine learning methods is presented, and a density map of applications in E-learning, manufacturing, and commerce is presented.
Journal ArticleDOI

Research on joint control of water pump and radiator of PEMFC based on TCO-DDPG

TL;DR: In this article , an approach based on deep reinforcement learning is proposed to address the fuel cell thermal management system's circulating water pump and radiator control issue, which adopts an improved updating delay strategy, optimized noise, and a classification experience playback and smooth target strategy to enhance algorithm robustness.
Journal ArticleDOI

Active Disturbance Rejection-Based Performance Optimization and Control Strategy for Proton-Exchange Membrane Fuel Cell System

Heng Wei, +1 more
- 15 Mar 2023 - 
TL;DR: In this article , an active disturbance rejection control strategy was proposed to maximize the net output power and realize better performance optimization and control of the oxygen excess ratio in a proton-exchange membrane fuel cell system.
References
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Journal ArticleDOI

Hybrid Model Predictive Control of the Step-Down DC–DC Converter

TL;DR: A hybrid converter model that is valid for the whole operating regime, and an a posteriori analysis proves, by deriving a piecewise-quadratic Lyapunov function, that the closed-loop system is exponentially stable.
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A content service deployment plan for metaverse museum exhibitions—Centering on the combination of beacons and HMDs

TL;DR: A service is established, which provides a virtual world experience by connecting a beacon installed in real space, that is, an exhibition room, to an HMD (head-mounted display), which incorporates a storytelling feature to diversify user experience by presenting the characteristics of and stories about artifacts.
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Adaptive Fuzzy-Neural-Network Design for Voltage Tracking Control of a DC–DC Boost Converter

TL;DR: In this paper, an adaptive fuzzy-neural-network control (AFNNC) scheme was designed for the voltage tracking control of a conventional dc-dc boost converter, which can be easily supplied to the duty cycle of the power switch in the boost converter without strict constraints on control parameters selection in conventional control strategies.
Journal ArticleDOI

A Multi-Agent Deep Reinforcement Learning Method for Cooperative Load Frequency Control of a Multi-Area Power System

TL;DR: Numerical simulations on a three-area power system and the fully-modeled New-England 39-bus system demonstrate that the proposed method can effectively minimize control errors against stochastic frequency variations caused by load and renewable power fluctuations.
Journal ArticleDOI

Novel hybrid fuzzy-PID control scheme for air supply in PEM fuel-cell-based systems

TL;DR: The results show that the novel hybrid fuzzy-PID controller performs significantly better than the classical PID controller and the FLC in terms of several key performance indices such as the Integral Squared Error (ISE), the Integrals Absolute Error (IAE) and theIntegral Time-weighted Absolute Error(ITAE).
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