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检索条件"任意字段=IEEE Data Driven Control and Learning Systems Conference"
28692 条 记 录,以下是191-200 订阅
排序:
Investigating Integral Reinforcement learning to Achieve Asymptotic Stability in Underactuated Mechanical systems
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ieee ROBOTICS AND AUTOMATION LETTERS 2024年 第1期9卷 191-198页
作者: Salamat, Babak Bencic, Daniel Elsbacher, Gerhard Seidel, Christian Tonello, Andrea M. Tech Hsch Ingolstadt AImot Inst D-85049 Ingolstadt Germany Alpen Adria Univ Klagenfurt Inst Networked & Embedded Syst A-9020 Klagenfurt Austria
This letter introduces an innovative data-driven integral reinforcement learning (IRL) algorithm for the control of a class of underactuated mechanical systems. We propose a novel value function that allows shaping an... 详细信息
来源: 评论
Harnessing Adaptive Sparsity: data-driven control for Solar PV Generation  12
Harnessing Adaptive Sparsity: Data-Driven Control for Solar ...
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12th International conference on Smart Grid (ICSmartGrid)
作者: Zhang, Zhongtian Khazaei, Javad Blum, Rick S. Lehigh Univ Elect & Comp Engn Bethlehem PA 18015 USA
This paper introduces a novel statistical learning method using adaptive regulated sparsity promotion for data-driven modeling and control of solar photovoltaic (PV) generation in smart grids. Unlike traditional data-... 详细信息
来源: 评论
Composite Multi-Vector Model Predictive control for Permanent Magnet Synchronous Motor  12
Composite Multi-Vector Model Predictive Control for Permanen...
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ieee 12th data driven control and learning systems conference (DDCLS)
作者: Gao, Lin Pan, Tianhong Anhui Univ Sch Elect Engn & Automat Hefei 230601 Peoples R China
Model Predictive control (MPC) has been widely used in the permanent magnet synchronous motor. However, in the finite control set MPC, only one voltage vector is applied, which leads to high current harmonics and torq... 详细信息
来源: 评论
The Q-Fractionalism Reasoning learning Method
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ieee TRANSACTIONS ON NEURAL NETWORKS AND learning systems 2025年 第1期36卷 1568-1582页
作者: Mazandarani, Mehran Jianfei, Pan Shenzhen Univ Dept Mechatron & Control Engn Shenzhen 518060 Peoples R China
As the title suggests, in this work, a modern machine learning method called the Q-fractionalism reasoning is introduced. The proposed method is founded upon a synergy of the Q-learning and fractional fuzzy inference ... 详细信息
来源: 评论
Predictive finite-time ADRC based longitudinal control for hypersonic aircraft with parametric uncertainties and unmodeled dynamics  12
Predictive finite-time ADRC based longitudinal control for h...
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ieee 12th data driven control and learning systems conference (DDCLS)
作者: Yang, Jinwei China West Normal Univ Sch Elect Informat Engn Nanchong 637009 Peoples R China
It is a significant issue to achieve the fast maneuverability and the strong robustness of hypersonic aircraft. Based on the thoughts of finite-time control and active disturbance rejection control (ADRC), this paper ... 详细信息
来源: 评论
Reinforcement learning based data-driven Optimal control Strategy for systems with Disturbance  12
Reinforcement Learning based Data-driven Optimal Control Str...
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ieee 12th data driven control and learning systems conference (DDCLS)
作者: Fan, Zhong-Xin Li, Shihua Liu, Rongjie Southeast Univ Sch Automat Nanjing 210096 Peoples R China Minist Educ Key Lab Measurement & Control Complex Syst Engn Nanjing 210096 Peoples R China Florida State Univ Dept Stat Tallahassee FL 32306 USA
This paper proposes a partially model-free optimal control strategy for a class of continuous-time systems in a datadriven way. Although a series of optimal control have achieving superior performance, the following c... 详细信息
来源: 评论
RBFNN-Based Event-Triggered data-driven Formation control for a Connected Heterogeneous Vehicle Platoon  13
RBFNN-Based Event-Triggered Data-Driven Formation Control fo...
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13th ieee data driven control and learning systems conference, DDCLS 2024
作者: Zhu, Panpan Jin, Shangtai Yin, Chenkun School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China
This paper presents a novel distributed data-driven control scheme for the longitudinal formation control of a connected heterogeneous vehicle (CHV) platoon. Initially, an event-triggered mechanism is devised to allev... 详细信息
来源: 评论
Dual Timescales Voltages Regulation in Distribution systems Using data-driven and Physics-based Optimization
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ieee TRANSACTIONS ON INDUSTRIAL INFORMATICS 2024年 第2期20卷 1259-1271页
作者: Zhang, Jian Cui, Mingjian He, Yigang Hefei Univ Technol Sch Elect & Automat Engn Hefei 230009 Peoples R China Tianjin Univ Sch Elect & Informat Engn Tianjin 300072 Peoples R China Wuhan Univ Sch Elect Engn & Automat Wuhan 430072 Peoples R China
A large number of electric vehicles (EVs), distributed solar and/or wind turbine generators (WTGs) connected to distribution systems lead to frequent and sharp voltages fluctuations. The action rates of conventional a... 详细信息
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Trajectory Tracking by an Adaptive controller for High-Speed Train Based on Neural Network and Sliding Mode control  12
Trajectory Tracking by an Adaptive Controller for High-Speed...
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ieee 12th data driven control and learning systems conference (DDCLS)
作者: Cen, Zhou Zhi, Li Yuan, Wangqing Fei, Sunpeng Xing, Guoyou Southwest Jiaotong Univ Sch Elect Engn Chengdu Peoples R China
This paper proposes an adaptive sliding mode controller (ASMC) for trajectory tracking of high-speed trains (HST) with uncertainties. The ASMC incorporates a radial basis function neural network (RBFNN) to approximate... 详细信息
来源: 评论
Distributed Model Free Adaptive Iterative learning control of Multiple HSTs Under DoS Attacks  12
Distributed Model Free Adaptive Iterative Learning Control o...
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ieee 12th data driven control and learning systems conference (DDCLS)
作者: Yu, Wei Cheng, Jungiang Huang, Deging Southwest Jiaotong Univ Sch Elect Engn Chengdu 610031 Peoples R China Europe Aisa Hitech & Digital Technol Co Ltd Zhengzhou 450000 Peoples R China
This paper studies the distributed model free adaptive iterative learning control (MFAILC) of multiple high-speed trains (MHSTs) under malicious denial-of-service (DoS) attacks. By using the equivalent linearization t... 详细信息
来源: 评论