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International Conference on Artificial Intelligence in Renewable Energetic Systems, IC-AIRES 2024

作者： Mawloud, Tellaa Abderrezak, Aibeche Zinelabidine, Doghmane Mohamed Madjid, Kidouche Automation and Electrification of Process Applied Automation Laboratory Faculty of Hydrocarbons Chemistry University M’Hamed Bougara Boumerdes35000 Algeria Institute of Electrical and Electronics Engineering University M’hamed Bougara Boumerdes Algeria Bob L. Herd Department of Petroleum Engineering Texas Tech University LubbockTX79401 United States

ISBN: (纸本)9783031803000

Stick-slip phenomena in the oil and gas drilling sector cause drillstring vibrations that provide major issues. These vibrations result in reduced drilling efficiency, equipment malfunctions, and possible dangers. This work introduces a thorough method for modeling and regulating stick-slip behavior. It utilizes a mechanical model with three degrees of freedom (3-DOF) that incorporates the influence of dry friction. The model combines both axial and torsional degrees of freedom to precisely reflect the intricate dynamics of the drillstring. Additionally, a control technique is suggested to alleviate stick-slip vibrations. This strategy involves using a hybrid Proportional-Integral-Derivative (PID) controller that has been tuned using Genetic Algorithms (GA). The PID-GA controller is specifically engineered to manage the rotating speed, mitigate stick-slip oscillations, and improve drilling stability. The efficacy of the suggested 3-DOF model and PID-GA control method in reducing stick-slip vibrations during drilling is proven by numerical simulations conducted under different drilling situations. The findings demonstrate notable advancements in drilling performance, such as decreased vibrations caused by friction, improved efficiency in drilling, and extended lifespan of the drillstring. This research significantly helps to the progress of drilling operations by offering a strong framework for modeling and managing stick-slip behavior. As a result, it improves drilling performance and guarantees operational safety in the oil and gas industry. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Gas industry

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Adaptive Consensus Quantized control for a Class of High-Order Nonlinear Multi-Agent Systems With Input Hysteresis and Full State Constraints

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1574-1589页

作者： Guoqiang Zhu Haoqi Li Xiuyu Zhang Chenliang Wang Chun-Yi Su Jiangping Hu the School of Automation Engineering Northeast Electric Power UniversityJilin 132012 the Jilin Province International Research Center of Precision Drive and Intelligent Control Jilin 132012China the School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China the Department of Mechanical and Industrial Engineering Concordia UniversityQCMontrealH3B 1R6Canada the School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China(

For a class of high-order nonlinear multi-agent systems with input hysteresis,an adaptive consensus output-feedback quantized control scheme with full state constraints is *** major properties of the proposed control scheme are:1)According to the different hysteresis input characteristics of each agent in the multi-agent system,a hysteresis quantization inverse compensator is designed to eliminate the influence of hysteresis characteristics on the system while ensuring that the quantized signal maintains the desired value.2)A barrier Lyapunov function is introduced for the first time in the hysteretic multi-agent *** constructing state constraint control strategy for the hysteretic multi-agent system,it ensures that all the states of the system are always maintained within a predetermined range.3)The designed adaptive consensus output-feedback quantization control scheme allows the hysteretic system to have unknown parameters and unknown disturbance,and ensures that the input signal transmitted between agents is the quantization value,and the introduced quantizer is implemented under the condition that only its sector bound property is *** stability analysis has proved that all signals of the closed-loop are semi-globally uniformly *** Star Sim hardware-in-the-loop simulation certificates the effectiveness of the proposed adaptive quantized control scheme.

关键词： Adaptive quantized control barrier Lyapunov function input hysteresis multi-agent systems

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Linear Fresnel reflector technology in Brazil: a techno-economic evaluation

Renewable Energy and Power Quality Journal

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Renewable Energy and Power Quality Journal 2023年 21卷 329-336页

作者： Azevedo, G.F. Lopes, M.E. Menezes, B.A. Rabelo, O.H.F. Brito, L.B. Dias, A.B. Filho, A.L.F. Domingues, E.G. Department of Electrical Engineering University of Brasília Darcy Ribeiro University Campus – Gleba A Avenida L3 Norte DF Brasília70.910-900 Brazil Electrical Engineering/Control and Automation Engineering Program Federal Institute of Goiás Câmpus Goiânia Rua 75 nº46-Centro GO Goiânia74055-110 Brazil

This study aims to present the results of applying a computational tool developed to perform a technical-economic feasibility analysis of a large-scale Linear Fresnel Reflector (LFR) solar power plant. The viability analysis indicators were obtained considering that the electricity produced trades at the Regulated Contracting Environment of the Brazilian Electricity Market. The parametric structural optimization method is used to optimize the technical parameters of the plant. A case study was conducted to analyze the viability of Implementing a 100 MW LFR power plant in the five regions of Brazil. The results indicated that Northeastern is the best region to install this power plant. However, the project is not viable in all cities analyzed. A sensitivity analysis (SA) of some strategically selected variables was conducted to evaluate its impacts on the project's net present value of an optimized LFR plant located in the city with the best technical performance. Finally, an optimistic scenario was evaluated considering the net present value's response to the parameters investigated in the SA. For this scenario, the results indicated the project's economic viability. © 2023, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

关键词： Sensitivity analysis

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Technical-economic feasibility analysis of a large-scale parabolic trough collectors solar power plant in Brazil

Renewable Energy and Power Quality Journal

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Renewable Energy and Power Quality Journal 2023年 21卷 337-344页

作者： Lopes, M.E. Azevedo, G.F. Menezes, B.A. Rabelo, O.H.F. Brito, L.B. Dias, A.B. Filho, A.L.F. Domingues, E.G. Department of Electrical Engineering University of Brasília Darcy Ribeiro University Campus Gleba A Avenida L3 Norte DF Brasília70.910-900 Brazil Electrical Engineering/Control and Automation Engineering Program Federal Institute of Goiás Câmpus Goiânia Rua 75 nº46-Centro GO Goiânia74055-110 Brazil

This study aims to present the results of the application of a computational tool developed to perform a technical-economic feasibility analysis of large-scale Parabolic Trough Collectors (PTC) solar power plants in Brazil. The gross revenue from cash flow is obtained through an energy trading model for the Regulated Contracting Environment of the Brazilian Electricity Market. The economic viability analysis uses the Net Present Value, Modified Internal Rate of Return, Discounted Payback, and Levelized Cost of Energy indicators. The parametric structural optimization method is used to optimize the technical parameters of the plant. A case study was conducted to analyse the feasibility of implementing a 100 MW PTC in the five regions of Brazil. The results indicated that the best region in Brazil to receive this technology is the northeastern region. However, the project is economically unfeasible in all cities analysed. Therefore, a sensitivity analysis of the main parameters that affect the project's net present value is carried out to evaluate the impact of the economic parameters on the economic viability of an optimized PTC plant located in the city with the best technical performance. An optimistic scenario was evaluated considering the system's response to the parameters investigated in the sensitivity analysis. For this scenario, the results pointed to the project's economic viability. © 2023, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

关键词： Sensitivity analysis

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Liquid refractive index measurement method based on orthogonal polarization laser self-mixing interference

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Optoelectronics Letters 2025年

作者： ZHAO Yan WANG Haipeng DU Shengzhi TONG Jigang KANG Jun School of Electrical Engineering and Automation， Tianjin University of Technology Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems Department of Electrical Engineering， Tshwane University of Technology

In this paper， a novel method combining orthogonal polarization laser self-mixing interference is proposed. The method utilizes a rotating cuvette to measure the refractive index of liquids at different concentrations. The cuvette is filled with the liquid to be measured and rotated by a certain angle. The change in the number of interference fringes， caused by comparing an empty cuvette with a liquid-filled cuvette， is used to calculate the refractive index of the liquid. A four-fold logic subdivision algorithm is then used to improve measurement resolution. The experimental results show that for pure water and different NaCl and glucose solutions concentrations， the average relative errors are 0.47%， 0.59%， and 2.17%， respectively， with the maximum relative error within ±2.54%. The standard deviation of all solutions is less than 3.4%.

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Weak feedback self-mixing interference fringe slope discrimination method based on deep learning

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Optoelectronics Letters 2025年

作者： ZHAO Yan LIN Maohua DU Shengzhi TONG Jigang LIU Bin HAN Fangfang School of Electrical Engineering and Automation， Tianjin University of Technology Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems Department of Electrical Engineering， Tshwane University of Technology

In order to identify the tilt direction of the self-mixing interference (SMI) signals under weak feedback regime interfered by noise， a deep learning method is proposed. The one-dimensional U-Net (1D U-Net) neural network can discriminate the direction of self-mixing fringes accurately and quickly. For experimental SMI signals， the 1D U-Net can be used for discriminant direction after a one-step normalization. Simulation and experimental results show that the proposed method is suitable for SMI signals with noise within the whole weak feedback regime， and can maintain a high discrimination accuracy for signals interfered by 5dB noise. Combined with fringe counting method， accurate and rapid SMI signal displacement reconstruction can be realized.

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Distributed Optimization with Finite Bit Adaptive Quantization for Efficient Communication and Precision Enhancement 63

Distributed Optimization with Finite Bit Adaptive Quantizati...

引用

63rd IEEE Conference on Decision and control, CDC 2024

作者： Rikos, Apostolos I. Jiang, Wei Charalambous, Themistoklis Johansson, Karl H. Artificial Intelligence Thrust of the Information Hub Guangzhou China The Hong Kong University of Science and Technology Department of Computer Science and Engineering Clear Water Bay Hong Kong Aalto University School of Electrical Engineering Department of Electrical Engineering and Automation Espoo Finland University of Cyprus School of Engineering Department of Electrical and Computer Engineering Nicosia1678 Cyprus Kth Royal Institute of Technology Division of Decision and Control Systems StockholmSE-100 44 Sweden

ISBN: (纸本)9798350316339

In realistic distributed optimization scenarios, individual nodes possess only partial information and communicate over bandwidth constrained channels. For this reason, the development of efficient distributed algorithms is essential. In our paper we addresses the challenge of unconstrained distributed optimization. In our scenario each node's local function exhibits strong convexity with Lipschitz continuous gradients. The exchange of information between nodes occurs through 3-bit bandwidth-limited channels (i.e., nodes exchange messages represented by a only 3 -bits). Our proposed algorithm respects the network's bandwidth constraints by leveraging zoom-in and zoom-out operations to adjust quantizer parameters dynamically. We show that during our algorithm's operation nodes are able to converge to the exact optimal solution. Furthermore, we show that our algorithm achieves a linear convergence rate to the optimal solution. We conclude the paper with simulations that highlight our algorithm's unique characteristics. © 2024 IEEE.

关键词： Bandwidth

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Data-Driven Human-Robot Interaction Without Velocity Measurement Using Off-Policy Reinforcement Learning

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 47-63页

作者： Yongliang Yang Zihao Ding Rui Wang Hamidreza Modares Donald C.Wunsch Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education School of Automation&Electrical EngineeringUniversity of Science and Technology BeijingBeijing 100083China School of Automation Beijng Institute TechnologyBeijing 100081China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Mechanical Engineering Department Michigan State UniversityEast LansingMI 48824 USA Department of Electrical&Computer Engineering Missouri University of Science&TechnologyRollaMO 65401 USA

In this paper,we present a novel data-driven design method for the human-robot interaction(HRI)system,where a given task is achieved by cooperation between the human and the *** presented HRI controller design is a two-level control design approach consisting of a task-oriented performance optimization design and a plant-oriented impedance controller *** task-oriented design minimizes the human effort and guarantees the perfect task tracking in the outer-loop,while the plant-oriented achieves the desired impedance from the human to the robot manipulator end-effector in the ***-driven reinforcement learning techniques are used for performance optimization in the outer-loop to assign the optimal impedance *** the inner-loop,a velocity-free filter is designed to avoid the requirement of end-effector velocity *** this basis,an adaptive controller is designed to achieve the desired impedance of the robot manipulator in the task *** simulation and experiment of a robot manipulator are conducted to verify the efficacy of the presented HRI design framework.

关键词： Adaptive impedance control data-driven method human-robot interaction(HRI) reinforcement learning velocity-free

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Triggered Mechanism for Strict Feedback Systems under Unknown control Directions 14

Triggered Mechanism for Strict Feedback Systems under Unknow...

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14th Asian control Conference, ASCC 2024

作者： Liu, Guilong Wu, Hongda Yang, Yongliang Xie, Wei Zhang, Weidong School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Department of Automation Shanghai200240 China

ISBN: (纸本)9789887581598

This paper presents an event-based asymptotic tracking control scheme designed for strict feedback systems with unknown control directions. The control directions directly determine how the controller acts on the system, thus impacting the system's stability and convergence speed. When the control directions are unknown, it presents a significant challenge in controller design. To tackle this issue, the Nussbaum-type gains are introduced. However, this method increases communication overhead. Hence, an event-triggered mechanism is introduced to alleviate this burden. Additionally, to achieve and maintain desired target states, satisfying control requirements and performance demands, this paper improves the event-triggered mechanism to achieve asymptotic tracking. Finally, the feasibility and effectiveness of the proposed design are validated through a simulation example. © 2024 Asian control Association.

关键词： Feedback

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Reinforcement Learning Behavioral control for Nonlinear Autonomous System

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1561-1573页

作者： Zhenyi Zhang Zhibin Mo Yutao Chen Jie Huang the College of Electrical Engineering and Automation Fuzhou UniversityFuzhou 350108 the Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian ProvinceFuzhou 350108 G+Industrial Internet Institute Fuzhou UniversityFuzhou 350108China

Behavior-based autonomous systems rely on human intelligence to resolve multi-mission conflicts by designing mission priority rules and nonlinear *** this work,a novel twolayer reinforcement learning behavioral control(RLBC)method is proposed to reduce such dependence by trial-and-error ***,in the upper layer,a reinforcement learning mission supervisor(RLMS)is designed to learn the optimal mission *** 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 *** the lower layer,a reinforcement learning controller(RLC)is designed to learn the optimal control *** with existing behavioral controllers,the RLC reduces the control cost of mission priority adjustment by balancing control performance and *** 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.

关键词： Behavioral control mission supervisor nonlinear autonomous system reinforcement learning

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