Results 31 to 40 of about 93,202 (286)
Robust oxygen excess ratio control of PEMFC systems using adaptive dynamic programming
Energy Reports, 2022 To improve the power generation efficiency and cells lifetime of proton exchange membrane fuel cells, the oxygen excess ratio (OER) control problem is investigated in this paper.
Jing Zhu +3 more
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SICE Journal of Control, Measurement, and System Integration, 2021 This paper considers trajectory tracking control for a nonholonomic mobile robot using integral reinforcement learning (IRL) based on a value functional represented by integrating a local cost.
Tatsuki Ashida, Hiroyuki Ichihara
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Data‐driven optimal scheduling for underground space based integrated hydrogen energy system
IET Renewable Power Generation, 2022 Integrated hydrogen energy systems (IHESs) have attracted extensive attention in mitigating climate problems. As a kind of large‐scale hydrogen storage device, underground hydrogen storage (UHS) can be introduced into IHES to balance the seasonal energy ...
Hengyi Li +4 more
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Entropy, 2022 In the field of reinforcement learning, we propose a Correct Proximal Policy Optimization (CPPO) algorithm based on the modified penalty factor β and relative entropy in order to solve the robustness and stationarity of traditional algorithms.
Weimin Chen +3 more
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IET Control Theory & Applications, 2023 This paper investigates the adaptive robust control problem based on reinforcement learning for an affine nonlinear system with unknown time‐varying uncertainty.
Wenxin Guo +3 more
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Approximate Policy Iteration with Bisimulation Metrics
, 2022 Bisimulation metrics define a distance measure between states of a Markov decision process (MDP) based on a comparison of reward sequences. Due to this property they provide theoretical guarantees in value function approximation (VFA). In this work we first prove that bisimulation and $π$-bisimulation metrics can be defined via a more general class of ...
Kemertas, Mete, Jepson, Allan
openaire +2 more sources
Entropy, 2023 This paper focuses on the optimal containment control problem for the nonlinear multiagent systems with partially unknown dynamics via an integral reinforcement learning algorithm.
Qiuye Wu, Yongheng Wu, Yonghua Wang
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Optimal Control of Iron-Removal Systems Based on Off-Policy Reinforcement Learning
IEEE Access, 2020 The goethite iron-removal process is an important procedure to remove the iron ions from the zinc hydrometallurgy. However, as a coherent system with complex reaction mechanism, associated uncertainties, and interconnected adjacent reactors, it is ...
Ning Chen +4 more
doaj +1 more source
Learning‐based control for discrete‐time constrained nonzero‐sum games
CAAI Transactions on Intelligence Technology, 2021 A generalized policy‐iteration‐based solution to a class of discrete‐time multi‐player non‐zero‐sum games concerning the control constraints was proposed. Based on initial admissible control policies, the iterative value function of each player converges
Chaoxu Mu, Jiangwen Peng, Yufei Tang
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‘Codes are not enough…’: a report of ongoing research [PDF]
, 2008 We consider the problem of rate allocation in a fading Gaussian multiple-access channel (MAC) with fixed transmission powers. Our goal is to maximize a general concave utility function of transmission rates over the throughput capacity region.
Eryilmaz, Atilla +3 more
core +4 more sources