Sanqing Qu - IEEE Xplore Author Profile

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Author details

Sanqing Qu

Publications

20

Citations

270

Publications by Year

20182024

Co-Authors:

Jiang BianZongtao BuGuang CHenKai ChenJörg Conradt

Show All Co-Authors (47)

Sanqing Qu

Affiliation

Tongji University

Publication Topics

Source Domain,
Target Domain,
Domain Adaptation,
Point Cloud,
Data Sources,
Domain Shift,
Generative Adversarial Networks,
Target Data,
3D Point Cloud,
Deep Neural Network,
Domain Adaptation Methods,
Dynamic Vision Sensor

Biography

Sanqing Qu received the B.E. degree in vehicle engineering from Tongji University, Shanghai, China, in 2020, where he is currently pursuing the Ph.D. degree in vehicle engineering. His research interests include computer vision, video understanding, and autonomous driving.(Based on document published on 15 December 2021).

Publications

20

Citations

270

Publications by Year

20182024

Co-Authors:

Jiang Bian
Zongtao Bu
Guang CHen
Kai Chen
Jörg Conradt

Show All Co-Authors (47)

Author's Published Works

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Showing 1-16 of 16 results

Conferences (11)

Journals (5)

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Ya-Fu Peng(15)
Chih-Min Lin(11)
Chun-Fei Hsu(4)
Rong-Jong Wai(4)
Chih-Hui Chiu(2)
Department of Electrical Engineering, Ching Yun University of Technology, Chungli, Taiwan(6)
Department of Electrical Engineering, Yuan-Ze University, Taoyuan, Taiwan(4)
Department of Electrical Engineering, Yuan-Ze University, Chungli, Taiwan(4)
Department of Electrical Engineering, Ching Yun University of Technology, Taoyuan, Taiwan(3)
Department of Electrical Engineering, Yuan-Ze University, Taiwan(3)
IEEE Transactions on Neural Networks(2)
2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583)(1)
2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)(1)
2005 IEEE International Conference on Industrial Technology(1)
2006 IEEE International Conference on Fuzzy Systems(1)
IEEE(16)
Vancouver, BC, Canada(2)
Brisbane, QLD, Australia(1)
Budapest, Hungary(1)
Hong Kong(1)
Kobe, Japan(1)
Control System(15)
Tracking Error(15)
Adaptive Control(12)
Optimal Control(10)
Memory Space(8)

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Results

WNN-based robust total-sliding-mode control for the synchronization of uncertain chaotic systems

Chiu-Hsiung Chen;Ya-Fu Peng;Sheng-Chieh Chung

2016 International Joint Conference on Neural Networks (IJCNN)

Year: 2016 | Conference Paper |

Cited by: Papers (1)

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A wavelet neural network (WNN)-based robust total-sliding-mode control scheme is developed for the synchronization of uncertain chaotic systems. The proposed control system offers a design method to drive the state trajectory to track a desired trajectory, and it is comprised of an adaptive WNN controller and a robust compensator. The adaptive WNN controller acts as the principal tracking controll...Show More

WNN-based robust total-sliding-mode control for the synchronization of uncertain chaotic systems

Chiu-Hsiung Chen;Ya-Fu Peng;Sheng-Chieh Chung

2016 International Joint Conference on Neural Networks (IJCNN)

Year: 2016 | Conference Paper |

Implementation of human conveyance vehicle using model-free AORCMAC control strategy

Chih Hui Chiu;Chun Chieh Chang;Ya Fu Peng

The 2012 International Joint Conference on Neural Networks (IJCNN)

Year: 2012 | Conference Paper |

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In this study, an adaptive output recurrent cerebellar model articulation controller (AORCMAC) is proposed for a human conveyance vehicle (HCV) control problem. A mechatronic system structure of the two wheels vehicle driven by two dc motors is briefly described. The main purpose of this paper is to develop a self-dynamic balancing and motion control strategy. Variable learning-rates for analytica...Show More

Implementation of human conveyance vehicle using model-free AORCMAC control strategy

Chih Hui Chiu;Chun Chieh Chang;Ya Fu Peng

The 2012 International Joint Conference on Neural Networks (IJCNN)

Year: 2012 | Conference Paper |

Adaptive intelligent tracking control system for uncertain nonlinear systems using ORCMAC

Ya-Fu Peng;Pin-Hsuan Huang;Cheng-Han Li

2008 International Conference on Machine Learning and Cybernetics

Year: 2008 | Conference Paper |

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In this paper, an adaptive intelligent tracking control (AITC) system employs an output recurrent cerebellar model articulation controller (ORCMAC) is developed for uncertain nonlinear system. In the AITC design, the Taylor linearization technique is employed to increase the learning ability of ORCMAC and the on-line adaptive laws are derived based on the Lyapunov stability analysis and the H℞ con...Show More

Adaptive intelligent tracking control system for uncertain nonlinear systems using ORCMAC

Ya-Fu Peng;Pin-Hsuan Huang;Cheng-Han Li

2008 International Conference on Machine Learning and Cybernetics

Year: 2008 | Volume: 7 | Conference Paper |

Design of Output Recurrent CMAC Backstepping Control System for Tracking Periodic Trajectories

Ya-Fu Peng;Ming-Hung Lin;Chao-Ming Chong

The 2006 IEEE International Joint Conference on Neural Network Proceedings

Year: 2006 | Conference Paper |

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An output recurrent cerebellar model articulation controller (ORCMAC) via the backstepping control technique is designed to control a linear ultrasonic motor (LUSM) for the tracking of periodic reference trajectories in this paper. The proposed ORCMAC has superior capability to the conventional cerebellar model articulation controller (CMAC) in efficient learning mechanism and dynamic response. In...Show More

Design of Output Recurrent CMAC Backstepping Control System for Tracking Periodic Trajectories

Ya-Fu Peng;Ming-Hung Lin;Chao-Ming Chong

The 2006 IEEE International Joint Conference on Neural Network Proceedings

Year: 2006 | Conference Paper |

Design and Implement of the Self-dynamic Controller for Two-wheel Transporter

Chih-Hui Chiu;Ya-Fu Peng

2006 IEEE International Conference on Fuzzy Systems

Year: 2006 | Conference Paper |

Cited by: Papers (4) | Patents (6)

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This paper describes the design and implement of a two-wheel transporter control system. In order to develop a self-dynamic balancing and motion control strategy, a fuzzy control algorithm has been proposed. Thus intelligent two-wheel transporter is demonstrated. Finally, experimental results prove that the proposed architecture can control the whole system very well.Show More

Design and Implement of the Self-dynamic Controller for Two-wheel Transporter

Chih-Hui Chiu;Ya-Fu Peng

2006 IEEE International Conference on Fuzzy Systems

Year: 2006 | Conference Paper |

Intelligent adaptive control scheme for uncertain nonlinear systems using H/sup /spl infin// control technique

Ya-Fu Peng;Chun-Fei Hsu;Chih-Min Lin;Chih-Hui Chiu

IEEE International Conference Mechatronics and Automation, 2005

Year: 2005 | Conference Paper |

Cited by: Papers (1)

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In this paper, an intelligent adaptive control system using an adaptive recurrent cerebellar model articulation controller (RCMAC) and based on H/sup /spl infin// control technique is developed for uncertain nonlinear system to achieve H/sup /spl infin// tracking performance. The proposed dynamic structure of RCMAC has superior capability to the conventional static cerebellar model articulation co...Show More

Intelligent adaptive control scheme for uncertain nonlinear systems using H/sup /spl infin// control technique

Ya-Fu Peng;Chun-Fei Hsu;Chih-Min Lin;Chih-Hui Chiu

IEEE International Conference Mechatronics and Automation, 2005

Year: 2005 | Volume: 4 | Conference Paper |

Intelligent tracking control for linear ultrasonic motor using H/sup /spl infin// control technique

Ya-Fu Peng;Chun-Fei Hsu;Chih-Min Lin;Ming-Hung Lin

2005 IEEE International Conference on Industrial Technology

Year: 2005 | Conference Paper |

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Since the dynamic characteristics of linear ultrasonic motor (LUSM) are highly nonlinear and time varying and the model is difficult to obtain, it is difficult to design a suitable controller to achieve high-precision position control by using the conventional control techniques. An intelligent tracking control system using an adaptive recurrent cerebellar model articulation controller (RCMAC) is ...Show More

Intelligent tracking control for linear ultrasonic motor using H/sup /spl infin// control technique

Ya-Fu Peng;Chun-Fei Hsu;Chih-Min Lin;Ming-Hung Lin

2005 IEEE International Conference on Industrial Technology

Year: 2005 | Conference Paper |

Missile guidance law design using adaptive cerebellar model articulation controller

Chih-Min Lin;Ya-Fu Peng

IEEE Transactions on Neural Networks

Year: 2005 | Volume: 16, Issue: 3 | Journal Article |

Cited by: Papers (64)

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An adaptive cerebellar model articulation controller (CMAC) is proposed for command to line-of-sight (CLOS) missile guidance law design. In this design, the three-dimensional (3-D) CLOS guidance problem is formulated as a tracking problem of a time-varying nonlinear system. The adaptive CMAC control system is comprised of a CMAC and a compensation controller. The CMAC control is used to imitate a ...Show More

Missile guidance law design using adaptive cerebellar model articulation controller

Chih-Min Lin;Ya-Fu Peng

IEEE Transactions on Neural Networks

Year: 2005 | Volume: 16, Issue: 3 | Journal Article |

Adaptive hybrid control for linear piezoelectric ceramic motor using recurrent CMAC network

Ya-Fu Peng;Chih-Min Lin;Rong-Jong Wai

2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583)

Year: 2004 | Conference Paper |

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In this study, an adaptive hybrid control system using a new cerebellar model articulation controller (CMAC) network paradigm called recurrent CMAC (RCMAC) network, which is proposed to control the moving table of the linear piezoelectric ceramic motor (LPCM) drive system to achieve high-precision position control with robustness. The architecture of RCMAC network is a modified model of the CMAC n...Show More

Adaptive hybrid control for linear piezoelectric ceramic motor using recurrent CMAC network

Ya-Fu Peng;Chih-Min Lin;Rong-Jong Wai

2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583)

Year: 2004 | Volume: 6 | Conference Paper |

Adaptive recurrent cerebellar model articulation controller for unknown dynamic systems with optimal learning-rates

Ya-Fu Peng;Chih-Min Lin;Wei-Liang Chin

2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)

Year: 2004 | Conference Paper |

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In this study, an adaptive recurrent cerebellar model articulation controller (ARCMAC) is designed for feedback control system with unknown dynamics. The proposed ARCMAC has superior capability to the conventional cerebellar model articulation controller (CMAC) in efficient learning mechanism, guaranteed system stability and dynamic response. Temporal relations are embedded in ARCMAC by adding fee...Show More

Adaptive recurrent cerebellar model articulation controller for unknown dynamic systems with optimal learning-rates

Ya-Fu Peng;Chih-Min Lin;Wei-Liang Chin

2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)

Year: 2004 | Volume: 2 | Conference Paper |

Adaptive hybrid control for linear piezoelectric ceramic motor drive using diagonal recurrent CMAC network

Rong-Jong Wai;Chih-Min Lin;Ya-Fu Peng

IEEE Transactions on Neural Networks

Year: 2004 | Volume: 15, Issue: 6 | Journal Article |

Cited by: Papers (44)

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This work presents an adaptive hybrid control system using a diagonal recurrent cerebellar-model-articulation-computer (DRCMAC) network to control a linear piezoelectric ceramic motor (LPCM) driven by a two-inductance two-capacitance (LLCC) resonant inverter. Since the dynamic characteristics and motor parameters of the LPCM are highly nonlinear and time varying, an adaptive hybrid control system ...Show More

Adaptive hybrid control for linear piezoelectric ceramic motor drive using diagonal recurrent CMAC network

Rong-Jong Wai;Chih-Min Lin;Ya-Fu Peng

IEEE Transactions on Neural Networks

Year: 2004 | Volume: 15, Issue: 6 | Journal Article |

Robust cerebellar model articulation controller design for unknown nonlinear systems

Chih-Min Lin;Ya-Fu Peng;Chun-Fei Hsu

IEEE Transactions on Circuits and Systems II: Express Briefs

Year: 2004 | Volume: 51, Issue: 7 | Journal Article |

Cited by: Papers (39)

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In this study, a robust cerebellar model articulation controller (RCMAC) is designed for unknown nonlinear systems. The RCMAC is comprised of a cerebellar model articulation controller (CMAC) and a robust controller. The CMAC is utilized to approximate an ideal controller, and the weights of the CMAC are on-line tuned by the derived adaptive law based on the Lyapunov sense. The robust controller i...Show More

Robust cerebellar model articulation controller design for unknown nonlinear systems

Chih-Min Lin;Ya-Fu Peng;Chun-Fei Hsu

IEEE Transactions on Circuits and Systems II: Express Briefs

Year: 2004 | Volume: 51, Issue: 7 | Journal Article |

Robust CMAC backstepping longitudinal control of vehicle platoons

Ya-Fu Peng;Chun-Fei Hsu;Chih-Min Lin;Chi-Jui Kao

IEEE International Conference on Networking, Sensing and Control, 2004

Year: 2004 | Conference Paper |

Cited by: Papers (5)

This paper proposes a control scheme for the car-following collision prevention systems using a robust cerebellar model articulation controller (CMAC) via the backstepping control technique. In the robust CMAC backstepping control system, an adaptive CMAC is used to mimic an ideal backstepping control law and a robust controller is designed to compensate for the difference between the ideal backst...Show More

Robust CMAC backstepping longitudinal control of vehicle platoons

Ya-Fu Peng;Chun-Fei Hsu;Chih-Min Lin;Chi-Jui Kao

IEEE International Conference on Networking, Sensing and Control, 2004

Year: 2004 | Volume: 1 | Conference Paper |

Adaptive CMAC-based supervisory control for uncertain nonlinear systems

Chih-Min Lin;Ya-Fu Peng

IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)

Year: 2004 | Volume: 34, Issue: 2 | Journal Article |

Cited by: Papers (158)

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An adaptive cerebellar-model-articulation-controller (CMAC)-based supervisory control system is developed for uncertain nonlinear systems. This adaptive CMAC-based supervisory control system consists of an adaptive CMAC and a supervisory controller. In the adaptive CMAC, a CMAC is used to mimic an ideal control law and a compensated controller is designed to recover the residual of the approximati...Show More

Adaptive CMAC-based supervisory control for uncertain nonlinear systems

Chih-Min Lin;Ya-Fu Peng

IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)

Year: 2004 | Volume: 34, Issue: 2 | Journal Article |

Implementation of LLCC-resonant driving circuit and adaptive CMAC neural network control for linear piezoelectric ceramic motor

Ya-Fu Peng;Rong-Jong Wai;Chih-Min Lin

IEEE Transactions on Industrial Electronics

Year: 2004 | Volume: 51, Issue: 1 | Journal Article |

Cited by: Papers (68)

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In this paper, an adaptive cerebellar-model articulation computer (CMAC) neural network (NN) control system is developed for a linear piezoelectric ceramic motor (LPCM) that is driven by an LLCC-resonant inverter. The motor structure and LLCC-resonant driving circuit of an LPCM are introduced initially. The LLCC-resonant driving circuit is designed to operate at an optimal switching frequency such...Show More

Implementation of LLCC-resonant driving circuit and adaptive CMAC neural network control for linear piezoelectric ceramic motor

Ya-Fu Peng;Rong-Jong Wai;Chih-Min Lin

IEEE Transactions on Industrial Electronics

Year: 2004 | Volume: 51, Issue: 1 | Journal Article |

Adaptive CMAC model reference control system for linear piezoelectric ceramic motor

Ya-Fu Peng;Rong-Jong Wai;Chih-Min Lin

Proceedings 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation. Computational Intelligence in Robotics and Automation for the New Millennium (Cat. No.03EX694)

Year: 2003 | Conference Paper |

Cited by: Papers (4)

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In this study, we present a design method for a model reference control structure using a cerebellar model articulation controller (CMAC). Since the dynamic characteristics and motor parameters of the linear piezoelectric ceramic motor (LPCM) are highly nonlinear and time-varying. An adaptive CMAC model reference control system is proposed to control the position of the moving table of the LPCM to...Show More

Adaptive CMAC model reference control system for linear piezoelectric ceramic motor

Ya-Fu Peng;Rong-Jong Wai;Chih-Min Lin

Proceedings 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation. Computational Intelligence in Robotics and Automation for the New Millennium (Cat. No.03EX694)

Year: 2003 | Volume: 1 | Conference Paper |

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