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第41届中国控制会议

作者： Yujie Cao Sheng Du Chengda Lu Min Wu Jinhua She School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Engineering Tokyo University of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Safe and efficient deep-sea drilling is inseparable from accurate and timely recognition of the ocean and geological *** refers to ocean dynamics,meteorology,hydrology,ecology,chemistry,ocean sound,light physical characteristics,ocean geology and geography.A complex ocean environment is one of the challenges facing ocean engineering at *** is difficult to establish an independent ocean or geological model for controller of the deep-sea drilling *** the face of complex and changeable ocean environment,modeling and analysis of wave environmental factors alone is not suitable for the control of deep-sea drilling *** paper analyzes the influence of various marine environmental factors on the offshore drilling platform and studies the internal relationship between each ***,the models of ocean breeze,wave and ocean current were designed to realize the simulation of ocean environment and parameterized description of ocean environment for deep-sea drilling *** has laid the foundation for the design of a deep-sea drilling control system.

关键词： Marine environment model Offshore drilling process Multi-model coupled

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Tunable Mid-Infrared Sensing Based on Graphene-Metal Hybrid Structure

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SSRN 2024年

作者： Wang, Xiaowei Chen, Zhihui Feng, Guang Wang, Yang Li, Shan Yang, Yibiao Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province College of Electronic Information and Optical Engineering Taiyuan University of Technology Taiyuan030024 China Taiyuan Institute of Technology Taiyuan030008 China Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education Institute of Biotechnology Shanxi University Taiyuan030006 China

Improving the emission efficiency of molecules or quantum dots is one of the effective means to improve the sensitivity of sensing. Here we provide a graphene-metal hybrid structure to achieve sensitivity detection in mid-infrared. The graphene-metal hybrid structure well coupling with a dipole source in mid-infrared was constructed. And then the high quality resonance peak can be detected. For different molecular detection applications, the resonance window can be controlled by geometrical parameters of metal structure in the mid-infrared range. Meanwhile the resonance wavelengths can be adjusted with graphene's chemical potential which can be controled through a varying gate voltage, and the emission enhancement ratio was 501 times on average. The hybrid structures also show excellent results in different background refractive indices. The sensitivity of the hybrid structure as a refractive index sensor reaches 6233 nm/RIU. All of our analyses show that the hybrid structure can be used as a better mid-infrared sensor. © 2024, The Authors. All rights reserved.

关键词： Graphene

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Hardware-in-the-loop Simulation and Experimental system for Process control of Marine Resources Exploration 43

Hardware-in-the-loop Simulation and Experimental System for ...

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43rd Chinese control Conference, CCC 2024

作者： Wang, Zeyi Wang, Chenxuan Ma, Zhejiaqi Zeng, Kanghui Lu, Chengda Wang, Yawu Wu, Min China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China China University of Geosciences School of Future Technology Wuhan430074 China

ISBN: (纸本)9789887581581

Effective control techniques are essential for offshore platform systems to suppress disturbances caused by the complex marine environment and ensure the stable operation of the systems during the exploration of marine resources. This paper establishes a hardware-in-the-loop based marine resource exploration process control simulation and experiment system to simulate the effects of marine environmental factors on the offshore platform. The marine environment is simulated using JONSWAP spectra and real marine environment data. The dynamics of offshore platform is modeled using Lagrange's equation method. And the control effect is demonstrated using virtual reality technology. Ultimately, the dynamic positioning system control experiment, which uses the equivalent input disturbance method, validates the experimental system. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Hardware-in-the-loop simulation

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Analysis and State Feedback control Bifurcation of Fractional-Order Cyclic Gene Regulatory Networks with Time Delay 41

Analysis and State Feedback Control Bifurcation of Fractiona...

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第41届中国控制会议

作者： Feng Liu Shujiang Sun Juan Zhao Feiyue Zhuo Hua O Wang School of Automation China University of Geosciences Engineering Research Center of Ministry of education for intelligent technology of earth exploration Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Mechanical Engineering Boston University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,a fractional-order cyclic gene regulatory network model with time delay is ***,the total time delay of the system is selected as the bifurcation parameter,and the condition for the existence of Hopf bifurcation is derived by analyzing its characteristic *** is found that the time delay affects the stability of the system,and the order affects the position of the bifurcation *** the time delay is greater than the critical time delay,the system loses ***,a state feedback controller is designed for the unstable *** is proved that the control method has good control effect for the system instability caused by Hopf ***,the correctness of the theoretical derivation is verified by simulation.

关键词： Fractional-order cyclic gene regulatory network Hopf bifurcation feedback control time delay

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Flow control for a Two-Stage Proportional Valve with Hydraulic Position Feedback

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Chinese Journal of Mechanical Engineering 2020年第6期33卷 64-76页

作者： He Wang Xiaohu Wang Jiahai Huang Long Quan Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of EducationTaiyuan University of TechnologyTaiyuan030024China Shanxi Transportation Technology Research&Development Co. LtdTaiyuan030024China

The current research mainly focuses on the flow control for the two-stage proportional valve with hydraulic position feedback which is named as Valvistor ***,the Valvistor valve is a proportional throttle valve and the flow fluctuates with the change of load *** flow fluctuation severely restricts the application of the Valvistor *** this paper,a novel flow control method the Valvistor valve is provided to suppress the flow fluctuation and develop a high performance proportional flow *** mathematical model of this valve is established and *** proportional-integral-derivative(PID)controller is adopted in the closed-loop flow control *** feedback is obtained by the flow inference with back-propagation neural network(BPNN)based on the spool displacement in the pilot stage and the pressure differential across the main *** results show that inference with BPNN can obtain the flow data fast and *** the flow control method,the flow can keep at the set point when the pressure differential across the main orifice *** flow control method is effective and the Valvistor valve changes from proportional throttle valve to proportional flow *** the developed proportional flow valve,the settling time of the flow is very short when the load pressure changes *** performances of hysteresis,linearity and bandwidth are in a high *** linear mathematical model can be verified and the assumptions in the system modeling is reasonable.

关键词： Flow control Proportional valve Hydraulic position feedback Back-propagation neural network

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LHMap-loc: Cross-Modal Monocular Localization Using LiDAR Point Cloud Heat Map

LHMap-loc: Cross-Modal Monocular Localization Using LiDAR Po...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Xinrui Wu Jianbo Xu Puyuan Hu Guangming Wang Hesheng Wang Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China Department of Engineering University of Cambridge Cambridge U.K

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Localization using a monocular camera in the pre-built LiDAR point cloud map has drawn increasing attention in the field of autonomous driving and mobile robotics. However, there are still many challenges (e.g. difficulties of map storage, poor localization robustness in large scenes) in accurately and efficiently implementing cross-modal localization. To solve these problems, a novel pipeline termed LHMap-loc is proposed, which achieves accurate and efficient monocular localization in LiDAR maps. Firstly, feature encoding is carried out on the original LiDAR point cloud map by generating offline heat point clouds, by which the size of the original LiDAR map is compressed. Then, an end-to-end online pose regression network is designed based on optical flow estimation and spatial attention to achieve real-time monocular visual localization in a pre-built map. In addition, a series of experiments have been conducted to prove the effectiveness of the proposed method. Our code is available at: https://***/IRMVLab/LHMap-loc.

关键词： Location awareness Point cloud compression Visualization Laser radar Accuracy Robot vision systems Real-time systems

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An Approach for Configuring Thermal Storage Capacity of Concentrated Solar Power Considering Low-Carbon Economic Dispatch

An Approach for Configuring Thermal Storage Capacity of Conc...

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International Conference on Power system Technology (POWERCON)

作者： Nuo Xu Xiaodong Chu Hua Ye Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan R.R. China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan P.R. China

Concentrated Solar Power (CSP) has gradually become an emerging development direction in the clean energy area because of its high energy efficiency, renewable and abundant nature. Thermal storage devices are used to regulate the power generation characteristics of CSP plants, and a rational configuration of thermal storage capacity can effectively reduce the system's carbon footprint. Considering the generation cost of thermal power generators, operation and maintenance cost of CSP plants, and system spinning reserve cost, a low-carbon economic dispatch scheme for power systems including CSP plants that takes carbon trading into account is proposed in this paper. On this basis, a thermal storage capacity allocation method for CSP plants is proposed, taking into account the thermal storage cost and dispatching cost. Additionally, simulation verification is performed on IEEE 30 network, and the findings demonstrate that the designed thermal storage capacity configuration strategy effectively reduces carbon emissions and overall system costs.

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Data-Driven Robust Optimization for Energy Chemical Processes under Uncertainties: A Review and Tutorial 4

Data-Driven Robust Optimization for Energy Chemical Processe...

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4th International Conference on Industrial Artificial Intelligence, IAI 2022

作者： Ning, Chao Li, Longyan Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Shanghai200240 China

ISBN: (数字)9781665451208

ISBN: (纸本)9781665451208

In recent years, data-driven robust optimization (DDRO) is becoming a popular and effective paradigm to address the challenging issue of uncertainty in energy chemical processes. This paper provides an overview of recent advances in the field of DDRO, with a primary focus on its methods and applications in process industries. Firstly, a brief introduction to various robust optimization model formulations and solution algorithms is presented. Secondly, research achievements of machine-learning enabled uncertainty sets, the corresponding DDRO, and variant techniques are summarized and analyzed in a systematic manner. Additionally, tutorial-like numerical examples are used to illustrate merits of DDRO compared with conventional robust optimization. Finally, fruitful applications of DDRO in energy chemical processes are encapsulated and categorized from domain perspectives. © 2022 IEEE.

关键词： Optimization

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SoftNeRF: A Self-Modeling Soft Robot Plugin for Various Tasks

SoftNeRF: A Self-Modeling Soft Robot Plugin for Various Task...

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IEEE/RSJ International Conference on intelligent Robots and systems (IROS)

作者： Jiwei Shan Yirui Li Qiyu Feng Ditao Li Lijun Han Hesheng Wang Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Building a self-model for robots, enabling them to simulate their physical selves and predict future states without direct interaction with the physical world, is crucial for robot motion planning and control. Existing self-modeling methods primarily focus on rigid robots and typically require significant time, effort, and resources to gather training data. In this study, we introduce SoftNeRF, a self-supervised visual self-model designed for soft robots. We use a hybrid neural shape representation based on the Signed Distance Function (SDF) to capture both the geometry and complex nonlinear motion of soft robots. By leveraging differentiable rendering, our method learns a self-model from readily available RGB images, similar to how humans understand their physical state through reflection. To improve training efficiency and model accuracy, we propose an error-guided adaptive sampling strategy. SoftNeRF can serve as a plug-in for various downstream tasks, even when trained with data unrelated to those tasks. We demonstrate SoftNeRF’s ability to support shape prediction and motion planning for robots in both simulated and real-world environments. Furthermore, SoftNeRF excels in detecting and recovering from damage, thereby enhancing machine resilience. Code is available at: https://***/irmvlab/soft-nerf.

关键词： Training Visualization Adaptation models Accuracy Shape Training data Soft robotics Rendering (computer graphics) Sampling methods Planning

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Adaptive Internal Time-Step Adjustment of Elementary Transfer Function Blocks for Trapezoidal Integration in Power system Dynamic Simulations

Adaptive Internal Time-Step Adjustment of Elementary Transfe...

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International Conference on Power system Technology (POWERCON)

作者： Yun Hang Changgang Li Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan Shandong China

With the development of renewable energy sources, the scale and complexity of power systems are continuously increasing, resulting in a high requirement for the efficiency of dynamic simulation. To enhance the overall simulation speed, this paper proposes an adaptive internal time-step adjustment method of elementary transfer function blocks for Trapezoidal integration in power system dynamic simulations. For blocks with different time constants, three integration modes are defined, including single-step integration, multiple-step integration, and static approximation. Each block can select an appropriate integration mode and adaptively adjust its internal time-step. Implementation of static approximation for blocks with small time constants is given. The proposed method is applied to the open-source Simulation Toolkit for Electrical Power systems (STEPS). The IEEE 9-bus test system is tested to obtain the maximum simulation time-step that can maintain numerical stability and validate the efficiency of the proposed method.

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