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610 results on '"Peng, Zhouhua"'

2. Safety-Critical Defensive Guidance of Autonomous Surface Vehicles for Domain Protection

Author

Kang, Tong, Gu, Nan, Wang, Dan, Peng, Zhouhua, Lv, Guanghao, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Jiang, Guo-Ping, editor, Wang, Mengyi, editor, and Ren, Zhang, editor

Published
2024
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3. Digital Twin Motion Modeling of an Autonomous Surface Vehicle Based on Meta-learning Predictor

Author

Xu, Jiaxue, Xia, Fengbei, Gu, Nan, Wang, Dan, Peng, Zhouhua, Lv, Guanghao, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Yu, Jianglong, editor, Liu, Yumeng, editor, and Li, Qingdong, editor

Published
2024
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14. Research on Construction of Open Online Courses System for Marine Engineering Major

Author

Wang, Haoliang, Wang, Baojun, Wu, Haojun, Peng, Zhouhua, Zhao, Junhao, Sun, Henan, Zhang, Hongpeng, Striełkowski, Wadim, Editor-in-Chief, Black, Jessica M., Series Editor, Butterfield, Stephen A., Series Editor, Chang, Chi-Cheng, Series Editor, Cheng, Jiuqing, Series Editor, Dumanig, Francisco Perlas, Series Editor, Al-Mabuk, Radhi, Series Editor, Scheper-Hughes, Nancy, Series Editor, Urban, Mathias, Series Editor, Webb, Stephen, Series Editor, Salleh, Kahirol Mohd, editor, Mohammad Ismail, Muhammad Ismath Ramzy, editor, and Yuan, Lizhuang, editor

Published
2023
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27. Event‐triggered obstacle avoidance control for autonomous surface vehicles with actuator faults.

Author

Dong, Gege, Hao, Li‐Ying, Li, Tieshan, and Peng, Zhouhua

Subjects
BACKSTEPPING control method, ACTUATORS, AUTONOMOUS vehicles
Abstract

The article addresses the event‐triggered obstacle avoidance control problem for autonomous surface vehicles subject to actuator faults. In order to tackle the challenges presented by unknown actuator faults, internal model uncertainties, and external disturbances, we propose a fault‐tolerant control scheme that relies on an extended state observer to estimate the unknown parameters. In addition, considering the occurrence of actuator faults, a novel event‐triggered mechanism is developed to reduce wear of actuator and ensures the performance of system. On this basis, we employ backstepping technique and an improved artificial potential function methods to develop an event‐triggered obstacle avoidance control scheme with the capability of fault tolerance. This proposed control strategy ensures the uniform ultimate boundedness of tracking errors. In contrast to existing results, the presented control strategy simultaneously holds the performance of obstacle avoidance and fault tolerance and reduce the update frequency of actuators. The effectiveness of the provided control scheme has been confirmed through simulation. [ABSTRACT FROM AUTHOR]

Published
2024
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40. Neurodynamics-Based Attack-Defense Guidance of Autonomous Surface Vehicles Against Multiple Attackers for Domain Protection

Author

Kang, Tong, Gu, Nan, Wang, Dan, Liu, Lu, Hu, Qing, and Peng, Zhouhua

Abstract

This article investigates an adversarial domain protection scenario involving multiple defending underactuated autonomous surface vehicles (ASVs) against an equal number of attacking ASVs in an obstructive environment. The defending ASVs can only obtain the positions of the attacking ASVs susceptible of stochastic measurement noises. A three-layer attack-defense guidance structure is proposed such that the defending ASVs are able to intercept the attacking ASVs with collision-free behaviors. In the first layer, an auction theory is utilized to achieve the attack-defense matching that efficiently assigns multiple defending ASVs to corresponding attacking ASVs in a distributed manner. In the second layer, an adaptive attack-defense guidance method is proposed, enabling each underactuated defending ASV to implement the appropriate guidance law aligned with the optimal interception point. In the last layer, a quadratic programming problem is formulated using speed-heading-constraint control barrier functions, and a neurodynamics optimization approach is employed to achieve real-time resolution of the optimal attack-defense guidance signal. The stability and safety analyses show that the system error is practically stochastic input-to-state stable, and the system is guaranteed to be safe. Experiment results demonstrate the effectiveness of the proposed neurodynamics-based attack-defense guidance method for domain protection.

Published
2024
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41. Event-Triggered Neural Adaptive Distributed Cooperative Control for the Multi-Tug Towing of Unactuated Offshore Platform with Uncertainties and Unknown Disturbances.

Author

Geng, Shaolong, Tuo, Yulong, Wang, Yuanhui, Peng, Zhouhua, and Wang, Shasha

Subjects
DRAG force, MACHINE learning, RADIAL basis functions, QUADRATIC programming, CLOSED loop systems
Abstract

An event-triggered neural adaptive cooperative control is proposed for the towing system (TS) with model parameter uncertainties and unknown disturbances. Different from ordinary multi-vessel formation control, the tugs and unactuated offshore platform in the TS are connected together by towlines, and the resultant tension of the towlines serves as the actual drag force for the platform. Initially, based on the radial basis function neural network (RBFNN), an adaptive RBFNN is designed to compensate unknown disturbances and model parameter uncertainties of the TS, and we use minimal learning parameter (MLP) algorithm to reduce the online learning parameters of adaptive RBFNN. Combined with dynamic surface technology and event-triggered control (ETC) mechanism, an event-triggered neural adaptive virtual controller is designed to obtain the desired drag force of the platform. According to the quadratic programming algorithm, the desired drag force is allocated as the desired tensions of towlines. Subsequently, the desired towline length and the desired position information of the tugs are obtained sequentially through the towline model and the position relationship between the tugs and the platform. Then, according to the desired positions of tugs, an event-triggered neural adaptive distributed cooperative controller is designed for achieving the multi-tug towing of the offshore platform. The ETC mechanism is introduced to reduce the communication burden within the TS and the execution frequency of the tugs' thrusters. Finally, the stability of the closed-loop system is proven using the Lyapunov theory, and the ETC mechanism proves that no Zeno behavior occurs. The effectiveness of the ETC mechanism and the MLP-based adaptive RBFNN on the controllers of TS is verified through simulations and comparison analysis. [ABSTRACT FROM AUTHOR]

Published
2024
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42. An Asymptotically Stable Identifier Design for Unmanned Surface Vehicles Based on Neural Networks and Robust Integral Sign of the Error

Author

Gao, Shengnan, Liu, Lu, Peng, Zhouhua, Wang, Dan, Gu, Nan, Jiang, Yue, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Lu, Huchuan, editor, Tang, Huajin, editor, and Wang, Zhanshan, editor

Published
2019
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43. Neural-Network-Based Modular Dynamic Surface Control for Surge Speed Tracking of an Unmanned Surface Vehicle Driven by a DC Motor

Author

Meng, Chengcheng, Liu, Lu, Peng, Zhouhua, Wang, Dan, Wang, Haoliang, Sun, Gang, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Lu, Huchuan, editor, Tang, Huajin, editor, and Wang, Zhanshan, editor

Published
2019
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44. Intelligent Fuzzy Kinetic Control for an Under-Actuated Autonomous Surface Vehicle via Stochastic Gradient Descent

Author

Jiang, Yue, Liu, Lu, Peng, Zhouhua, Wang, Dan, Gu, Nan, Gao, Shengnan, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Lu, Huchuan, editor, Tang, Huajin, editor, and Wang, Zhanshan, editor

Published
2019
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