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Wei-Fu Su - IEEE Xplore Author Profile

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Author details

Wei-Fu Su

Publications

9

Citations

50

Publications by Year

20132024

Co-Authors:

Pang-Jen ChiangPei-Shuo ChiuPei-Hong GuHsiang-Yu HsiehChe-Jung Hsu

Show All Co-Authors (16)

Wei-Fu Su

Affiliation

Department of Electrical Engineering

Kun Shan University

Tainan, Taiwan

Publication Topics

Feasible Solution,
Objective Function,
Assessment Of Efficiency,
Average Computation Time,
Behavior Of Flies,
Cable System,
Circuit Design,
Conversion Efficiency,
Core Loss,
Cross-linked Polyethylene,
Current Flow,
Current Strategies

Biography

Wei-Fu Su received the B.S. degree in electrical engineering from the National Taiwan University of Science and Technology, Taipei, Taiwan, in 1990, and the M.S. and Ph.D. degrees in electrical engineering from National Cheng Kung University, Tainan, Taiwan, in 1992 and 2001, respectively. Since 1992, he has been with the Department of Electrical Engineering, Kun Shan University, Tainan, Taiwan, where he is currently a Professor. His research interests include power quality, power system analysis, power electronics, and renewable energy.(Based on document published on 14 August 2024).

Publications

9

Citations

50

Publications by Year

20132024

Co-Authors:

Pang-Jen Chiang
Pei-Shuo Chiu
Pei-Hong Gu
Hsiang-Yu Hsieh
Che-Jung Hsu

Show All Co-Authors (16)

Author's Published Works

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Showing 1-25 of 130 results

Conferences (102)

Journals (28)

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Tao Zhang(127)
Jingyan Song(14)
Yu Cheng(9)
Huangang Wang(9)
Ziwei Wang(8)
Department of Automation, Tsinghua University, Beijing, China(72)
Department of Automation, School of Information Science and Technology, Tsinghua University, Beijing, China(14)
Department of Automation, Tsinghua University, Beijing(9)
High-Tech Institute of Xi’an, Xi’an, China(5)
Department of Electrical Engineering, Tsinghua University, Beijing, PR China(5)
2013 IEEE International Conference on Robotics and Biomimetics (ROBIO)(4)
2017 36th Chinese Control Conference (CCC)(4)
IEEE Access(4)
The 27th Chinese Control and Decision Conference (2015 CCDC)(4)
2009 IEEE International Conference on Robotics and Biomimetics (ROBIO)(3)
IEEE(130)
Media(5)
Code(1)
Beijing, China(9)
Qingdao, China(7)
Hangzhou, China(6)
Shenzhen, China(6)
Guilin, China(5)
Neural Network(18)
Angular Velocity(14)
Simulation Results(11)
Control Strategy(10)
Convolutional Neural Network(10)

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Results

A Developed LSTM-Ladder-Network-Based Model for Sleep Stage Classification

Ruichen Li;Bei Wang;Tao Zhang;Takenao Sugi

IEEE Transactions on Neural Systems and Rehabilitation Engineering

Year: 2023 | Volume: 31 | Journal Article |

Cited by: Papers (11)

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Sleep staging is crucial for diagnosing sleep-related disorders. The heavy and time-consuming task of manual staging can be released by automatic techniques. However, the automatic staging model would have a relatively poor performance when working on unseen new data due to individual differences. In this research, a developed LSTM-Ladder-Network (LLN) model is proposed for automatic sleep stage c...Show More

A Developed LSTM-Ladder-Network-Based Model for Sleep Stage Classification

Ruichen Li;Bei Wang;Tao Zhang;Takenao Sugi

IEEE Transactions on Neural Systems and Rehabilitation Engineering

Year: 2023 | Volume: 31 | Journal Article |

Camera Attributes Control for Visual Odometry With Motion Blur Awareness

Bin Han;Yicheng Lin;Yan Dong;Hao Wang;Tao Zhang;Chengyuan Liang

IEEE/ASME Transactions on Mechatronics

Year: 2023 | Volume: 28, Issue: 4 | Journal Article |

Cited by: Papers (6)

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The practical application of visual odometry (VO) is challenging under High Dynamic Range (HDR) environments which has a significant impact on the quality of feature point tracking. There are two key attributes that affect the image quality of a camera, namely exposure time and gain. The goal of camera attributes control research is to design algorithms that can actively adjust camera acquisition ...Show More

Camera Attributes Control for Visual Odometry With Motion Blur Awareness

Bin Han;Yicheng Lin;Yan Dong;Hao Wang;Tao Zhang;Chengyuan Liang

IEEE/ASME Transactions on Mechatronics

Year: 2023 | Volume: 28, Issue: 4 | Journal Article |

Collision Avoidance Among Dense Heterogeneous Agents Using Deep Reinforcement Learning

Kai Zhu;Bin Li;Wenming Zhe;Tao Zhang

IEEE Robotics and Automation Letters

Year: 2023 | Volume: 8, Issue: 1 | Journal Article |

Cited by: Papers (15)

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Navigating in a complex congested social environment without collision is a crucial and challenging task. Recent studies have demonstrated the considerable success of Deep Reinforcement Learning (DRL) in multi-agent collision avoidance. However, the assumption of these studies that agents are homogeneous circles deviates from reality, leading to performance deterioration in congested scenarios. Th...Show More

Collision Avoidance Among Dense Heterogeneous Agents Using Deep Reinforcement Learning

Kai Zhu;Bin Li;Wenming Zhe;Tao Zhang

IEEE Robotics and Automation Letters

Year: 2023 | Volume: 8, Issue: 1 | Journal Article |

Prediction of Material Removal Rate Using Phase Partition and Semi-supervised Regression

Chunpu Lv;Jingwei Huang;Huangang Wang;Tao Zhang

2022 China Automation Congress (CAC)

Year: 2022 | Conference Paper |

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In the Chemical Mechanical Planarization (CMP) process, the Material Removal Rate (MRR) is an important indicator of polishing performance. However, MRR is difficult to be measured. Therefore, Virtual Metrology (VM) methods to predict MRR by process variables have become a hot topic. Conventional VM methods extract the global statistical characteristics of the CMP process, ignoring its multi-phase...Show More

Prediction of Material Removal Rate Using Phase Partition and Semi-supervised Regression

Chunpu Lv;Jingwei Huang;Huangang Wang;Tao Zhang

2022 China Automation Congress (CAC)

Year: 2022 | Conference Paper |

Automatic Sleep Staging Method Based on EEG Signal and its Optimized Feature Space

Meng Yang;Ruichen Li;Bei Wang;Tao Zhang

2022 7th International Conference on Intelligent Informatics and Biomedical Science (ICIIBMS)

Year: 2022 | Conference Paper |

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Sleep is essential for physical and mental health. One's overnight sleep is usually evaluated into different sleep stages consisting of several sleep cycles. Computerized sleep staging would be an efficient tool but the performance is still required to be developed. In this study, an automatic sleep staging method is realized based on EEG signal and its optimized feature space. Several characteris...Show More

Automatic Sleep Staging Method Based on EEG Signal and its Optimized Feature Space

Meng Yang;Ruichen Li;Bei Wang;Tao Zhang

2022 7th International Conference on Intelligent Informatics and Biomedical Science (ICIIBMS)

Year: 2022 | Volume: 7 | Conference Paper |

Hybrid Gait Recognition Method Based on Phase Trajectory

Pinjie Li;Tao Xue;Tao Zhang;Huangang Wang;Ming Zhang

2022 27th International Conference on Automation and Computing (ICAC)

Year: 2022 | Conference Paper |

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Gait recognition is critical to the activity monitoring, health management, assistance control of prostheses and exoskeletons, etc. This study aims to improve the gait classification performance on daily hybrid locomotions. We found the hip angle phase trajectories present significantly gait-dependent patterns, whereas the phase patterns show repeated limit cycles for periodic gaits while half-cyc...Show More

Hybrid Gait Recognition Method Based on Phase Trajectory

Pinjie Li;Tao Xue;Tao Zhang;Huangang Wang;Ming Zhang

2022 27th International Conference on Automation and Computing (ICAC)

Year: 2022 | Conference Paper |

Material Removal Rate Prediction with Phase Sensitive Variables Selection and Phase Partition

Chunpu Lv;Tao Zhang;Huangang Wang

2022 27th International Conference on Automation and Computing (ICAC)

Year: 2022 | Conference Paper |

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In the Chemical Mechanical Planarization (CMP) process of the semiconductor industry, high accuracy prediction of Material Removal Rate (MRR) is essential to achieve wafer-to-wafer (W2W) control. Therefore, data-driven Virtual Metrology (VM) methods for MRR prediction have received much attention. Traditional methods focus on extracting features from raw data along the time dimension. However, a C...Show More

Material Removal Rate Prediction with Phase Sensitive Variables Selection and Phase Partition

Chunpu Lv;Tao Zhang;Huangang Wang

2022 27th International Conference on Automation and Computing (ICAC)

Year: 2022 | Conference Paper |

Real-time Gait Trajectory Prediction Based on Convolutional Neural Network with Multi-head Attention

Jie Yin;Tao Xue;Tao Zhang

2022 27th International Conference on Automation and Computing (ICAC)

Year: 2022 | Conference Paper |

Cited by: Papers (1)

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The lower limb exoskeleton can effectively improve the ability of users. Accurate gait trajectory prediction can enhance the effect of lower limb exoskeletons. The current gait trajectory prediction methods have the disadvantages of insufficient prediction accuracy and long calculation time. This paper proposes a convolutional neural network model with multi-head attention to predict the gait traj...Show More

Real-time Gait Trajectory Prediction Based on Convolutional Neural Network with Multi-head Attention

Jie Yin;Tao Xue;Tao Zhang

2022 27th International Conference on Automation and Computing (ICAC)

Year: 2022 | Conference Paper |

Development and Experimental Validation of a Passive Exoskeletal Vest

Zihao Du;Zefeng Yan;Tiantian Huang;Ou Bai;Qin Huang;Tao Zhang;Bin Han

IEEE Transactions on Neural Systems and Rehabilitation Engineering

Year: 2022 | Volume: 30 | Journal Article |

Cited by: Papers (9)

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Passive upper limb exoskeletons are often designed to relieve muscle fatigue of manufacturing workers. Existing exoskeletons often provide partial assistance, and their assistive torque is only affected by elastic elements and mechanisms, which, however, are not sufficient because of the changing load of the shoulder joint due to the motion of the elbow and the weight of various tools. To improve ...Show More

Development and Experimental Validation of a Passive Exoskeletal Vest

Zihao Du;Zefeng Yan;Tiantian Huang;Ou Bai;Qin Huang;Tao Zhang;Bin Han

IEEE Transactions on Neural Systems and Rehabilitation Engineering

Year: 2022 | Volume: 30 | Journal Article |

Distributed Architecture of Power Grid Asset Management and Future Research Directions

Tao Zhang;Xing Yan;Renmin Zhang;Qingquan Ye;Junhua Ma

Year: 2022 | Volume: 10 | Journal Article |

Cited by: Papers (7)

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With the continuous expansion of the power system scale, the requirements of the power system intelligence are getting higher and higher and the power grid fault diagnosis has been made to become the focus of the power system research. In this paper, the research field of power grid fault diagnosis is reviewed, and the data sources and characteristics and data preprocessing are analyzed. Moreover,...Show More

Distributed Architecture of Power Grid Asset Management and Future Research Directions

Tao Zhang;Xing Yan;Renmin Zhang;Qingquan Ye;Junhua Ma

Year: 2022 | Volume: 10 | Journal Article |

Collision-Free Trajectory Planning for a 6-DoF Free-Floating Space Robot via Hierarchical Decoupling Optimization

Shengjie Wang;Yuxue Cao;Xiang Zheng;Tao Zhang

IEEE Robotics and Automation Letters

Year: 2022 | Volume: 7, Issue: 2 | Journal Article |

Cited by: Papers (15)

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Collision-free trajectory planning is a critical technique for space robot mission. In this letter, we developed a model-free Hierarchical Decoupling Optimization (HDO) algorithm to realize 6D-pose multi-target trajectory planning for the free-floating space robot. In order to reduce the complexity of exploration, the whole system consists of two layers: the high-level policy completes the collisi...Show More

Collision-Free Trajectory Planning for a 6-DoF Free-Floating Space Robot via Hierarchical Decoupling Optimization

Shengjie Wang;Yuxue Cao;Xiang Zheng;Tao Zhang

IEEE Robotics and Automation Letters

Year: 2022 | Volume: 7, Issue: 2 | Journal Article |

Optimal Scheduling Strategy of Virtual Power Plant With Power-to-Gas in Dual Energy Markets

Tao Zhang;Zechun Hu

IEEE Transactions on Industry Applications

Year: 2022 | Volume: 58, Issue: 2 | Journal Article |

Cited by: Papers (37)

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The virtual power plant (VPP) is a cloud-based aggregator that combines heterogeneous distributed energy resources to give a reliable and friendly power supply. In this article, a VPP that consists of natural gas network, power to gas (P2G) equipment, flexible load, and other resources is introduced in the electricity market and natural gas market considering the uncertainties of renewable energy ...Show More

Optimal Scheduling Strategy of Virtual Power Plant With Power-to-Gas in Dual Energy Markets

Tao Zhang;Zechun Hu

IEEE Transactions on Industry Applications

Year: 2022 | Volume: 58, Issue: 2 | Journal Article |

Trajectory Tracking for a Dual-Arm Free-Floating Space Robot With a Class of General Nonsingular Predefined-Time Terminal Sliding Mode

Yicheng Liu;Wen Yan;Tao Zhang;Chunxiao Yu;Haiyan Tu

IEEE Transactions on Systems, Man, and Cybernetics: Systems

Year: 2022 | Volume: 52, Issue: 5 | Journal Article |

Cited by: Papers (43)

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This paper addresses trajectory planning and control for a dual-arm free-floating space robot (FFSR) based on predefinedtime stability. Firstly, a class of general nonsingular terminal sliding mode control strategy is proposed to achieve global predefined-time stability by switching a control parameter in a form of function. Then, a high-precision trajectory planning method is proposed for a FFSR ...Show More

Trajectory Tracking for a Dual-Arm Free-Floating Space Robot With a Class of General Nonsingular Predefined-Time Terminal Sliding Mode

Yicheng Liu;Wen Yan;Tao Zhang;Chunxiao Yu;Haiyan Tu

IEEE Transactions on Systems, Man, and Cybernetics: Systems

Year: 2022 | Volume: 52, Issue: 5 | Journal Article |

Adversarial Learning-Based Automatic Evaluator for Image Captioning

Qianxia Ma;Duo Wang;Pinjie Li;Jingyan Song;Tao Zhang

2021 China Automation Congress (CAC)

Year: 2021 | Conference Paper |

Cited by: Papers (1)

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Image captioning imitates the process of humans describing the visual world using natural language. Evaluating image captioning remains a challenging task. Current methods mainly focus on the similarity between the generated description and reference texts, despite the direct relevance of the caption and the corresponding image. In this paper, we propose an adversarial learning-based evaluator. Th...Show More

Adversarial Learning-Based Automatic Evaluator for Image Captioning

Qianxia Ma;Duo Wang;Pinjie Li;Jingyan Song;Tao Zhang

2021 China Automation Congress (CAC)

Year: 2021 | Conference Paper |

Roof Supports Measurement in Coal Mining by 3D Registration and Model Fitting

Yan Dong;Tao Zhang;Yongqiang Wang;Xingfu Zhang;Jun Zhu;Xin Yang;Bin Han

2021 China Automation Congress (CAC)

Year: 2021 | Conference Paper |

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The roof support, a type of special equipment for coal mining, protect miners and other facilities in fully mechanized working face under the ground, and move with shearers when extracting coal. The states of each support, such as the position, height and tilt angle are important for its motion control. Unfortunately, it is difficult to measure these parameters directly in the working face. The no...Show More

Roof Supports Measurement in Coal Mining by 3D Registration and Model Fitting

Yan Dong;Tao Zhang;Yongqiang Wang;Xingfu Zhang;Jun Zhu;Xin Yang;Bin Han

2021 China Automation Congress (CAC)

Year: 2021 | Conference Paper |

TransRAM: A classification model of breast pathology images that imitates the diagnosis process of pathologists

Weiming Mi;Tao Zhang;Jiaming Wang

2021 China Automation Congress (CAC)

Year: 2021 | Conference Paper |

Cited by: Papers (2)

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Breast cancer, one of the most common health threats to females worldwide, has always been a crucial topic in the medical field. However, manual diagnosis suffers a series of challenges, such as considerable time cost and low diagnosis consistency. In this paper, we proposed TransRAM, which merited both Transformers and Recurrent Models of Visual Attention, as a strong alternative for digital path...Show More

TransRAM: A classification model of breast pathology images that imitates the diagnosis process of pathologists

Weiming Mi;Tao Zhang;Jiaming Wang

2021 China Automation Congress (CAC)

Year: 2021 | Conference Paper |

Resonance Impedance Shaping Control of Hip Robotic Exoskeleton

Tao Xue;Ming Zhang;Jie Yin;Meng Zhang;Ou Bai;Ziwei Wang;Tao Zhang

2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

Year: 2021 | Conference Paper |

Cited by: Papers (1)

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The hip assistance robotic exoskeleton has been demonstrated as an effective device to assist elderly and disabled people with gait disorders. The assistance efficiency of these devices, however, is less optimized because the parameters in the active impedance control are manually designated. This paper presented a novel assistance control scheme to address the sub-optimal issue. This study poses ...Show More

Resonance Impedance Shaping Control of Hip Robotic Exoskeleton

Tao Xue;Ming Zhang;Jie Yin;Meng Zhang;Ou Bai;Ziwei Wang;Tao Zhang

2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

Year: 2021 | Conference Paper |

Exploration and Practice of an Innovative Idea and Method of Organized Engineering Education

Tao Zhang;Haiyan Huang;Feng Chen

2021 IEEE Frontiers in Education Conference (FIE)

Year: 2021 | Conference Paper |

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This Innovate Practice Full Paper presents an innovative idea and method of organized engineering education. With the rapid globalization of China's economy, and especially the emergence of a large number of innovative large-scale enterprises supported by advanced technology, a great number of engineering-proficient talents is urgently needed. However, there is a disparity between the talent culti...Show More

Exploration and Practice of an Innovative Idea and Method of Organized Engineering Education

Tao Zhang;Haiyan Huang;Feng Chen

2021 IEEE Frontiers in Education Conference (FIE)

Year: 2021 | Conference Paper |

A Multi-Target Trajectory Planning of a 6-DoF Free-Floating Space Robot via Reinforcement Learning

Shengjie Wang;Xiang Zheng;Yuxue Cao;Tao Zhang

2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Year: 2021 | Conference Paper |

Cited by: Papers (13)

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Space robots have played an essential role in space junk removal. Compared with traditional model-based methods, model-free reinforcement learning methods are promising in tackling space capture missions, which is challenging due to the dynamic singular problem and measuring errors of dynamics parameters. Nevertheless, current research mostly focus on the single-target environment. In this paper, ...Show More

A Multi-Target Trajectory Planning of a 6-DoF Free-Floating Space Robot via Reinforcement Learning

Shengjie Wang;Xiang Zheng;Yuxue Cao;Tao Zhang

2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Year: 2021 | Conference Paper |

Remaining Useful Life Estimation for Turbofan Engine with Transformer-based Deep Architecture

Qianxia Ma;Ming Zhang;Yuchun Xu;Jingyan Song;Tao Zhang

2021 26th International Conference on Automation and Computing (ICAC)

Year: 2021 | Conference Paper |

Cited by: Papers (11)

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With the development of information technology and sensors, the large industrial system has become a data-rich environment, which leads to the rapid development and application of deep learning for the remaining useful life prediction, especially for the turbofan engine. Currently, the deep architecture of CNN, LSTM have been used to address the RUL estimation of a turbofan engine. However, they a...Show More

Remaining Useful Life Estimation for Turbofan Engine with Transformer-based Deep Architecture

Qianxia Ma;Ming Zhang;Yuchun Xu;Jingyan Song;Tao Zhang

2021 26th International Conference on Automation and Computing (ICAC)

Year: 2021 | Conference Paper |

An End-to-End Trajectory Planning Strategy for Free-floating Space Robots

Shengjie Wang;Yuxue Cao;Xiang Zheng;Tao Zhang

2021 40th Chinese Control Conference (CCC)

Year: 2021 | Conference Paper |

Cited by: Papers (6)

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The traditional trajectory planning methods of free-floating space robots have the dynamic singular problem and the difficulty of accurate modeling. Although learning-based approaches have achieved remarkable performance on such task, they mainly focus on single modular design such as the perception, planning, or control part. Optimization-based end-to-end method can well combine perception, plann...Show More

An End-to-End Trajectory Planning Strategy for Free-floating Space Robots

Shengjie Wang;Yuxue Cao;Xiang Zheng;Tao Zhang

2021 40th Chinese Control Conference (CCC)

Year: 2021 | Conference Paper |

Three-Dimensional Area Coverage with UAV Swarm based on Deep Reinforcement Learning

Zhiyu Mou;Yu Zhang;Feifei Gao;Huangang Wang;Tao Zhang;Zhu Han

ICC 2021 - IEEE International Conference on Communications

Year: 2021 | Conference Paper |

Cited by: Papers (3)

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In this paper, we study the fast coverage problem of 3D irregular terrain surfaces with a hierarchical UAV swarm. We first build a 3D model of a random irregular terrain and project the 3D terrain surface into many weighted 2D patches. Then we develop a two-level hierarchical UAV swarm architecture, including the low-level follower UAVs (FUAVs) and the high-level leader UAVs (LUAVs). For FUAVs, we...Show More

Three-Dimensional Area Coverage with UAV Swarm based on Deep Reinforcement Learning

Zhiyu Mou;Yu Zhang;Feifei Gao;Huangang Wang;Tao Zhang;Zhu Han

ICC 2021 - IEEE International Conference on Communications

Year: 2021 | Conference Paper |

Deep Reinforcement Learning Based Three-Dimensional Area Coverage With UAV Swarm

Zhiyu Mou;Yu Zhang;Feifei Gao;Huangang Wang;Tao Zhang;Zhu Han

IEEE Journal on Selected Areas in Communications

Year: 2021 | Volume: 39, Issue: 10 | Journal Article |

Cited by: Papers (57)

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Unmanned aerial vehicle (UAV) technology is recognized as a promising solution to area coverage problems (ACPs) and has been extensively studied recently. In this paper, we study the 3D irregular terrain surface coverage problem with a hierarchical UAV swarm. We first build the 3D model of a random irregular terrain and propose a geometric way to project the 3D terrain surface into many weighted 2...Show More

Deep Reinforcement Learning Based Three-Dimensional Area Coverage With UAV Swarm

Zhiyu Mou;Yu Zhang;Feifei Gao;Huangang Wang;Tao Zhang;Zhu Han

IEEE Journal on Selected Areas in Communications

Year: 2021 | Volume: 39, Issue: 10 | Journal Article |

Statistical Feature Extraction and Hybrid Feature Selection for Material Removal Rate Prediction in Chemical Mechanical Planarization Process

Wenlan Jiang;Chunpu Lv;Bing Yang;Fuquan Zhang;Ying Gao;Tao Zhang;Huangang Wang

2021 5th IEEE Electron Devices Technology & Manufacturing Conference (EDTM)

Year: 2021 | Conference Paper |

Cited by: Papers (5)

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The prediction for average Material Removal Rate (MRR) in Chemical Mechanical Planarization (CMP) process has been recognized to be critical for working condition identification in semiconductor manufacturing. This paper focuses on feature engineering in virtual metrology (VM) for MRR prediction. A statistical feature extraction method is proposed, and a two-step hybrid feature selection method is...Show More

Statistical Feature Extraction and Hybrid Feature Selection for Material Removal Rate Prediction in Chemical Mechanical Planarization Process

Wenlan Jiang;Chunpu Lv;Bing Yang;Fuquan Zhang;Ying Gao;Tao Zhang;Huangang Wang

2021 5th IEEE Electron Devices Technology & Manufacturing Conference (EDTM)

Year: 2021 | Conference Paper |

Event-Triggered Prescribed-Time Fuzzy Control for Space Teleoperation Systems Subject to Multiple Constraints and Uncertainties

Ziwei Wang;Hak-Keung Lam;Bo Xiao;Zhang Chen;Bin Liang;Tao Zhang

IEEE Transactions on Fuzzy Systems

Year: 2021 | Volume: 29, Issue: 9 | Journal Article |

Cited by: Papers (58)

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Limited by the operation time window and working space, space teleoperation tasks need to be completed within an expected time while ensuring that the end effector meets the physical constraints. Meanwhile, the interaction with unknown environments would cause uncertainty in the closed-loop system, which brings great challenges to the control design. To solve the above problems, the control perfor...Show More

Event-Triggered Prescribed-Time Fuzzy Control for Space Teleoperation Systems Subject to Multiple Constraints and Uncertainties

Ziwei Wang;Hak-Keung Lam;Bo Xiao;Zhang Chen;Bin Liang;Tao Zhang

IEEE Transactions on Fuzzy Systems

Year: 2021 | Volume: 29, Issue: 9 | Journal Article |

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