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5th IEEE International Conference on Technology, Informatics, Management, engineering and Environment, TIME-E 2024

作者： Albert Panggabean, Good Fried Romadhon, Rahmat Lubis, Ramot Joelianto, Endra Institut Teknologi Bandung Doctoral Program in Engineering Physics Bandung Indonesia Institut Teknologi Del Faculty of Informatics and Electrical Engineering Toba Indonesia Institut Teknologi Bandung Engineering Physics Study Program Bandung Indonesia Institut Teknologi Bandung Instrumentation Control and Automation Research Group Bandung Indonesia

ISBN: (纸本)9798350364743

In indoor vertical farming systems, managing dynamic and complex environments poses significant challenges. Traditional control strategies often fall short in adapting to rapid changes in critical parameters such as nutrient levels, climate conditions, and plant health indicators. To address these challenges, this paper presents a novel approach for optimizing indoor vertical farming using Deep Deterministic Policy Gradient (DDPG), a reinforcement learning algorithm well-suited for environments with continuous action spaces. Our study focused on the control and monitoring of key parameters, including nutrient levels (pH and EC), climate conditions (temperature, humidity, light, and CO2 levels), and plant health indicators (biomass accumulation and leaf size structure). By defining a comprehensive state and action space, we simulated an indoor farming environment and trained the DDPG model to maximize crop yield and health. © 2024 IEEE.

关键词： DDPG indoor vertical farming precision agriculture reinforcement learning smart farming

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LiDAR Point Cloud Map Coding Framework Based on Quadric Surface Fitting and Scene Construction 5

LiDAR Point Cloud Map Coding Framework Based on Quadric Surf...

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5th IEEE International Conference on Pattern Recognition and Machine Learning, PRML 2024

作者： Sun, Xuebin Wang, Jinxi Yang, Xiaofei School of Electrical Automation and Information Engineering Tianjin University Tianjin China School of Information and Control Engineering China University of Mining and Technology Xuzhou China Shanghai Institute of Optics and Fine Mechanics Department of Aerospace Laser Technology and System Shanghai China

ISBN: (纸本)9798350355925

Due to rapid 3D acquisition advancements, LiDAR point clouds are prevalent in emerging applications like heritage preservation, mobile robotics, and remote sensing. Yet, the sheer data volume poses challenges for transmission and storage, especially in autonomous driving. This paper introduces an efficient coding framework for compressing large dense LiDAR point cloud maps. By recording timestamps and quaternion matrices during map construction, we reduce map compression to sequence compression. The scans are segregated into intra-frames and inter-frames. For intra-frames, a quadric surface fitting intra-prediction technique eliminates spatial redundancy. For inter-frames, by constructing the 3D scene using encoded intra-frames, the inter-frame can be simulated according to its posture and LiDAR intrinsic parameters. Coding focuses on the difference between actual and predicted point cloud data. Decoding reverses this process, reconstructing the point cloud map from the decoded sequence and quaternion matrices. KITTI dataset experiments show the point cloud map can be averagely compressed to 3.43% of its original size while maintaining centimeter-level precision. This outperforms both octree and Google Draco methods. © 2024 IEEE.

关键词： Mobile robots

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Extended NNs-Based Adaptive Event-Triggered Asymptotic control for Nonlinear systems Against Actuator Faults 7

Extended NNs-Based Adaptive Event-Triggered Asymptotic Contr...

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7th International Symposium on Autonomous systems, ISAS 2024

作者： Liu, Shanlin Zhang, Yingwei Zhao, Xudong Wang, Hesheng Northeastern University College of Information Science and Engineering Shenyang China Northeastern University State Laboratory of Synthesis Automation of Process Industry Shenyang China Dalian University of Technology Faculty of Electronic Information and Electrical Engineering Dalian China 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

ISBN: (纸本)9798350363173

In this article, an adaptive event-triggered asymp¬totically fault-tolerant control (FTC) issue for nonlinear systems with actuator faults is investigated. An extended neural networks (NNs) technique is introduced to estimate unknown functions of the system under consideration. Compared with traditional NNs that ignore approximation errors, the proposed extended NNs further processes approximation errors, reducing the conservatism of the proposed algorithm. Then, within the framework of backstepping method, a new adaptive control strategy is developed by combining event-triggered mechanism (ETM) and bound estimation (BE) approach, which ensures the asymptotic convergence of system states while also reducing the transmission of unnecessary information, thus improving the utilization of communication resources. At the same time, the designed controller eliminates the adverse effects of actuator failures and system nonlinear terms. Finally, a simulation example of a single-link robot system is provided to demonstrate that the developed control strategy can ensure that all signals are bounded and system states are asymptotically convergent. © 2024 IEEE.

关键词： Approximation algorithms

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Identifiability Analysis of Load Model Parameters by Estimating Confidential Intervals

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CSEE Journal of Power and Energy systems 2023年第5期9卷 1666-1675页

作者： Xinran Zhang Chao Lu Ying Wang Qiantu Ruan Hongbo Ye Weihong Wang the School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China. the State Key Laboratory of Control and Simulation of Power System and Generation Equipment Tsinghua UniversityBeijing 100084China School of Technology Beijing Forestry UniversityBeijing 100083China the State Grid Shanghai Electric Power Company Shanghai 200122China

The identification of load model parameters from practical measurement data has become an essential method to build load models for power system simulation,analysis and *** practical situations,the accuracy of the load model parameters identification results is impacted by data quality and measurement accuracy,which leads to the problem of *** this paper,an identifiability analysis methodology of load model parameters,by estimating the confidential intervals(CIs)of the parameters,is *** load model structure and the combined optimization and regression method to identify the parameters are first ***,the definition and analysis method of identifiability are *** CIs of the parameters are estimated through the profile likelihood method,based on which a practical identifiability index(PII)is defined to quantitatively evaluate ***,the effectiveness of the proposed analysis approach is validated by the case study results in a practical provincial power *** results show that the impact of various disturbance magnitudes,measurement errors and data length can all be reflected by the proposed ***,the proposed PII can provide guidance in data length selection in practical load model identification situations.

关键词： Confidential interval Load modeling parameter estimation practical identifiability

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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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Fuzzy-Cycle: Visible to Infrared Ship Image Translation Based on CycleGAN 6

Fuzzy-Cycle: Visible to Infrared Ship Image Translation Base...

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6th International Conference on Industrial Artificial Intelligence, IAI 2024

作者： He, Long Yu, Yue Liu, Chang Sun, Yangyang Jiang, Feng Hu, Xiaoning Pan, Chengwei Dong, Xiwang School of Artificial Intelli-gence Beihang University Beijing China Beijing Institute of Control and Electronic Technology Beijing China School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University School of Artificial Intelligence Institute of Unmanned System Beijing China

ISBN: (纸本)9798350356618

Detecting targets in infrared ship images is crucial for various applications, such as maritime rescue and ship inspection. Training contemporary mainstream detection and segmentation models, however, requires large-scale, high-quality infrared ship image datasets. In open-world maritime confrontation scenarios, the complex and variable environment, scarcity of target ships, and limited acquisition conditions make it challenging to construct high-quality infrared ship image datasets. To address this issue, this paper proposes an unpaired visible-infrared ship image translation model based on CycleGAN, named Fuzzy-Cycle. The model introduces a fuzzy cycle loss to encourage the model to learn feature mapping rules between different domains while minimizing attention to unnecessary features. Additionally, the method employs U-Net as the generator network to retain shallow image features during upsampling and selects PatchGAN as the discriminator network, embedding Haar wavelet transform to enhance the discriminator's ability to analyze image frequency domain features. Experiments on the VAIS dataset demonstrate that the proposed algorithm outperforms mainstream unpaired image transfer models, showing excellent performance in the task of visible-infrared ship image translation. Furthermore, zero-shot image translation experiments on the HRSC2016 dataset prove the generalizability and reliability of the proposed method. © 2024 IEEE.

关键词： Wavelet transforms

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Stability Analysis of Boolean Networks: Exploring the Influence of Multi-bit Function Perturbations 63

Stability Analysis of Boolean Networks: Exploring the Influe...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Liu, Aixin Wang, Lin Chen, Guanrong Guan, Xinping Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China City University of Hong Kong Department of Electrical Engineering Hong Kong

ISBN: (纸本)9798350316339

This study investigates the impact of multi-bit function perturbations (MFPs) on the steady-state distribution of Boolean networks (BNs), with a focus on robust stability. First, the algebraic formulation of BNs under MFPs is introduced. Then, a novel stability criterion is proposed, demonstrating that monotonically decreasing perturbations can effectively ensure the stability of BNs against MFPs. A significant advantage of this approach is that it enables robust stability assessment without remodeling the perturbed BNs. Applying this methodology to a simplified Boolean model of the lactose operon in Escherichia coli reveals that MFPs can serve as strategic tools to promote stability within BNs, rather than being merely disruptive. © 2024 IEEE.

关键词： Stability criteria

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Practical Distance-Based Formation Stabilization and Tracking of Nonholonomic Multi-agent systems 7th

Practical Distance-Based Formation Stabilization and Tracki...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Tang, Xiangyu Yu, Jianglong Dong, Xiwang Yang, Xiangyu Ren, Zhang School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789819733279

This paper investigates practical distance-based formation stabilization and tracking issues for nonholonomic multi-agent systems (MASs). Firstly, the agent’s nonholonomic kinematics is represented as a left invariant system on a Lie group. Through the introduction of an auxiliary state and a virtual control guided by the transverse function method, the original system is effectively converted into a fully actuated one. Secondly, under the assumption of infinitesimal and minimal rigidity in the graph, a gradient-descent-based virtual controller is devised for the transformed MASs, facilitating practical rigid formation stabilization. Thirdly, a discontinuous distributed velocity estimator is designed for formation tracking. The nonholonomic MASs achieve the desired formation shape while effectively tracking the reference trajectory. Finally, the effectiveness of the proposed method is verified by numerical examples. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Multi agent systems

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A Cloud-Edge-Based Multi-Label Learning and Fast Clustering Method for Emerging New PV Faults 13

A Cloud-Edge-Based Multi-Label Learning and Fast Clustering ...

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13th IEEE International Conference on CYBER Technology in automation, control, and Intelligent systems, CYBER 2023

作者： Liu, Qi Yang, Bo Liu, Yuxiang Ma, Kai Guan, Xinping Shanghai Jiao Tong University Ministry of Education Key Laboratory of System Control and Information Processing Department of Automation Shanghai200240 China School of Electrical Engineering Yanshan University Qinhuangdao066004 China

ISBN: (纸本)9798350315196

Aiming at accurate identification of emerging new faults in PV systems, a novel PV fault diagnosis framework based on cloud-edge collaboration is designed. Model updates are deployed on the cloud servers, while real-time diagnosis is implemented at the edge devices. A multi-label learning model is developed to extract fault features efficiently, and a threshold scheme is further designed for feature enhancement. The obtained features are processed by K-Means clustering and the One-Class Support Vector Machine (OCSVM) methods, which can accurately diagnose existing types and identify unknown faults. For analysis and demonstration, the Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE) methods are used for dimensionality reduction and visualization. Numerical results validate the effectiveness of the proposed method. © 2023 IEEE.

关键词： K-means clustering

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