Jie Huang

Fuzhou University

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Yutao Chen

Fuzhou University

Ning Zhou

University of Science and Technology of China

Yiwen Qi

Shenyang Aerospace University

Riqing Chen

Fujian Agriculture and Forestry University

Guoqing Tian

Fuzhou University

Zhenyi Zhang

State Ethnic Affairs Commission

Dingci Lin

Fuzhou University

Dongfang Li

Fuzhou University

Yuanqing Xia

Beijing Institute of Technology

Zhenyi Zhang

Zhejiang University of Science and Technology

Cooperative Institutions

Fuzhou University

Chinese Academy of Sciences

Beijing Institute of Technology

Shanghai Jiao Tong University

Tsinghua University

Central South University

University of Science and Technology of China

Education Department of Fujian Province

Zhejiang University

Harbin Institute of Technology

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Adaptive predefined‐time tracking control for high‐order strict‐feedback nonlinear systems with unknown mismatched disturbances

International Journal of Adaptive Control and Signal Processing (2022)

Fanlin Jia Jie Huang Xiao He

Summary The problem of practical predefined‐time tracking control is con sidered for high‐order strict‐feedback nonlinear systems subject to unknown mismatched disturbances. The exact bound of the mismatched disturbances is unknown in this study. A novel adaptive predefined‐time tracking control strategy based on backstepping is proposed by applying a predefined time stability theory. Using the designed tracking controller, all signals are bounded, and a user‐defined bound on the tracking error is ensured in a predefined interval, independent of initial states. The estimation parameters associated with the upper bound of the disturbances are updated adaptively, making the system robust to the disturbances. Simulation studies are conducted to illustrate the performance of the proposed control strategy.

Tracking (education)

Tracking error

10.1002/acs.3502

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Citations (7)

Output regulation of nonlinear systems with nonhyperbolic zero dynamics

Jie Huang Ching‐Fang Lin

Previous solvability conditions for the output regulation of nonlinear systems are applicable only to those with hyperbolic zero dynamics. It is shown in this note that output regulation of nonlinear systems with nonhyperbolic zero dynamics is also possible by a reduction of plant dynamics and an augmentation of the exosystem.< >

Zero (linguistics)

Dynamics

10.1109/cdc.1994.411462

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Citations (2)

Efficient path planning with neuro-genetic-fuzzy approach

Automation, Robotics and Control Systems (2009)

Khelchandra Thongam Jie Huang

Source

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Citations (0)

Dynamic Control Authority Allocation in Indirect Shared Control for Steering Assistance

IEEE Transactions on Intelligent Transportation Systems (2025)

Yutao Chen Hongliang Zhang Haocong Chen Jie Huang Bin Wang

10.1109/tits.2024.3520107

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A Robust Non-Cooperative Control Approach for Human-Machine Shared Driving

2021 China Automation Congress (CAC) (2024)

Qiteng Hong Jie Huang Yutao Chen

10.1109/cac63892.2024.10865190

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Analysis of Over-Obstacle Robot with Left and Right Wheel Sharing one Shaft

Peng-Fei Yin Yujun Wang Jie Huang

The wheeled robot whose left and right sides are in phase (L&R in-phase) is superior to the one whose both sides are not in getting over obstacles.Nevertheless, the wheeled robot has to abandon its routine swerve way depending on speed difference of the left and right wheels.In this paper, we present two methods of swerve, one is terms with different friction coefficient on both sides and the other is differential wheel diameter.The quadruple wheeled robot makes its first two wheels revolving and the rest couple reversing.With such rotating mode, there exists a slight deviation [1] on both sides in every cycle because of its different parameters.After several periods, the wheeled robot swerves as instructed.Furthermore, we perform a series of experiments to test this structure we have proposed how the obstacle climbing capability and swerve efficiency are.We also compare the results with the performance of conventional structure whose left and right wheels are out of phase

Left and right

10.2991/aeece-16.2016.49

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Intelligent recognition method for working-cycle state of hydraulic excavator

Journal of ZheJiang University (Engineering Science) (2019)

Jie Huang Dong Wang Xinqing Wang Qin Yin Faming Shao

Excavator

10.3785/j.issn.1008-973x.2019.09.004

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Citations (4)

Human Decision-Making Modeling and Cooperative Controller Design for Human–Agent Interaction Systems

IEEE Transactions on Human-Machine Systems (2022)

Jie Huang Wenhua Wu Zhenyi Zhang Guoqing Tian Song Zheng

In this article, the problem of human intervention and autonomous controller design for human–agent interaction systems is addressed. In particular, a human drift diffusion model is developed for second-order linear multiagent systems subject to unknown external disturbances. The proposed human drift diffusion model can model human decision-making behavior using multiple sources of human decision-making information. Accurate human intervention timing is obtained by setting varying thresholds for different decision-making information. In addition, a fixed-time sliding mode adaptive behavioural controller is developed to execute human decisions in the framework of the null-space based behavioral control method. The controller guarantees that agents can follow human commands given an arbitrary initial task error and can finish tasks in fixed time. A simulation under various scenarios shows that the proposed human drift diffusion model is able to provide appropriate human intervention and the proposed controller can guarantee human command fulfillment within fixed time.

10.1109/thms.2022.3185333

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Citations (6)

Distributed adaptive finite-time fault-tolerant cooperative control of heterogeneous multi-agent systems with saturation and disturbances

International Journal of Systems Science (2024)

Shangkun Liu Bin Jiang Zehui Mao Youmin Zhang Jie Huang

In this paper, the issue of distributed adaptive finite-time fault-tolerant cooperative control (FT-FTCC) problem is investigated for multiple unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) with unknown parameter uncertainties, actuator faults, input saturation and external disturbances. Starting from the dynamic models of the UAVs and UGVs, an unified control model is presented. Then, a sliding-mode estimator is presented to estimate the position of the leader for the followers which only uses the information from neighbours. Next, a distributed adaptive FT-FTCC scheme, which can also deal with the uncertainties, actuator faults, input saturation and disturbances, is proposed by utilising disturbance observers and neural networks. Based on Lyapunov function approach, the tracking errors of all followers subject to the pre-defined desired positions are uniformly ultimately bounded. Finally, simulations are given to validate the efficiency of the developed FT-FTCC scheme.

Saturation (graph theory)

10.1080/00207721.2024.2427848

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Reinforcement Learning Behavioral Control for Nonlinear Autonomous System

IEEE/CAA Journal of Automatica Sinica (2022)

Zhenyi Zhang Zhibin Mo Yutao Chen Jie Huang

Behavior-based autonomous systems rely on human intelligence to resolve multi-mission conflicts by designing mission priority rules and nonlinear controllers. In this work, a novel two-layer reinforcement learning behavioral control (RLBC) method is proposed to reduce such dependence by trial-and-error learning. Specifically, in the upper layer, a reinforcement learning mission supervisor (RLMS) is designed to learn the optimal mission priority. Compared with existing mission supervisors, the RLMS improves the dynamic performance of mission priority adjustment by maximizing cumulative rewards and reducing hardware storage demand when using neural networks. In the lower layer, a reinforcement learning controller (RLC) is designed to learn the optimal control policy. Compared with existing behavioral controllers, the RLC reduces the control cost of mission priority adjustment by balancing control performance and consumption. All error signals are proved to be semi-globally uniformly ultimately bounded (SGUUB). Simulation results show that the number of mission priority adjustment and the control cost are significantly reduced compared to some existing mission supervisors and behavioral controllers, respectively.

Supervisor

10.1109/jas.2022.105797

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Citations (15)