Chenfeng Huang

ORCID: 0000-0003-3779-525X
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Research Areas
  • Adaptive Control of Nonlinear Systems
  • Distributed Control Multi-Agent Systems
  • Underwater Vehicles and Communication Systems
  • Neural Networks Stability and Synchronization
  • Control and Dynamics of Mobile Robots
  • Robotic Path Planning Algorithms
  • Potato Plant Research
  • Plant nutrient uptake and metabolism
  • Stability and Control of Uncertain Systems
  • Adaptive Dynamic Programming Control
  • Maritime Navigation and Safety
  • Iterative Learning Control Systems
  • Smart Grid Security and Resilience
  • Advanced Computational Techniques and Applications
  • Vehicle Dynamics and Control Systems
  • Advanced Control Systems Optimization
  • Network Security and Intrusion Detection
  • Grey System Theory Applications
  • Rough Sets and Fuzzy Logic
  • Nonlinear Dynamics and Pattern Formation
  • Dynamics and Control of Mechanical Systems
  • Advanced Data Storage Technologies
  • Advanced Control Systems Design
  • Plant Molecular Biology Research

Dalian Maritime University
2018-2025

Huazhong Agricultural University
2024

Ministry of Agriculture and Rural Affairs
2024

North China Electric Power University
2011

In this note, a novel adaptive constrained control algorithm is proposed for dynamic positioning vessels in the presence of input amplitude and rate saturations. scheme, both kinematics kinetics loops are augmented by auxiliary system to deal with saturation impact. Meanwhile, merits command filters minimal leering parameter technique, cumbersome analytic derivatives virtual law need not be required design, only two parameters updated online stabilise effect model uncertainty external...

10.1049/iet-cta.2018.5036 article EN IET Control Theory and Applications 2018-10-04

In this article, a robust adaptive dynamic position-control problem is addressed for full-actuated surface vessels under coupled uncertainties from unmodeled hydrodynamic effects and time-varying external disturbances. To obtain high-performance position controller, reinforcement learning (RL) weights law involving actor critic networks designed without knowledge of the model dynamics disturbance parameters. This can enhance robustness closed-loop control system. Furthermore, integrated to...

10.3390/jmse13050993 article EN cc-by Journal of Marine Science and Engineering 2025-05-21

Summary In this paper, an adaptive distributed parallel formation control approach is proposed for a group of underactuated marine surface vehicles with actuator fault and limited input. Firstly, the algebraic topology employed to model intervehicle communication network multiple vehicles. Both uncertainties environmental disturbance satisfying norm‐bounded conditions are discussed. Secondly, concise bounded‐feedback law developed compensate supremum neural weight matrix, rather than each...

10.1002/asjc.2911 article EN Asian Journal of Control 2022-07-20

This paper focuses on the intervehicle security-based robust formation control of unmanned surface vehicles (USVs) to implement switch mission. In scheme, a novel adaptive potential ship (APS)-based guidance principle is developed prevent collisions, which common and threatening when maneuvering switch. By employing artificial field (APF), APS can program real-time attitude reference for USVs by using security distance while achieving path-following task. As part, algorithm proposed...

10.3390/jmse11051020 article EN cc-by Journal of Marine Science and Engineering 2023-05-10

10.1007/s11771-011-0945-6 article EN Journal of Central South University of Technology 2011-12-01

Nitrogen (N) is crucial for plant growth, available primarily as nitrate (NO3-) and ammonium (NH4+). However, its presence in soil often limited, leading to N deficiency plants. Therefore, ensuring a suitable source vital enhance growth uptake. The interaction between NO3- NH4+ supporting Brassica napus remains poorly understood. In this study, we assessed genotypic differences among 49 varieties of B. when exposed or alone, combination at different ratios through nutrient solution culture....

10.2139/ssrn.4828574 preprint EN 2024-01-01
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