检索结果-内蒙古大学图书馆

Distributionally robust optimization based chance-constrained energy management for hybrid energy powered cellular networks

引用

Digital Communications and Networks 2023年第3期9卷 797-808页

作者： Pengfei Du Hongjiang Lei Imran Shafique Ansari Jianbo Du Xiaoli Chu The Engineering Research Center of Intelligent Air-ground Integrated Vehicle and Traffic Control Ministry of EducationXihua UniversityChengdu610039China Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and TelecommunicationsChongqing400065China James Watt School of Engineering University of GlasgowGlasgowG128QQUK Shaanxi Key Laboratory of Information Communication Network and Security Xi'an University of Posts and TelecommunicationsXi'an710121China Electronic and Electrical Engineering University of SheffieldSheffieldS102TNUK

Energy harvesting has been recognized as a promising technique with which to effectively reduce carbon emis-sions and electricity expenses of base ***,renewable energy is inherently stochastic and inter-mittent,imposing formidable challenges on reliably satisfying users'time-varying wireless traffic *** addition,the probability distribution of the renewable energy or users’wireless traffic demand is not always fully known in *** this paper,we minimize the total energy cost of a hybrid-energy-powered cellular network by jointly optimizing the energy sharing among base stations,the battery charging and discharging rates,and the energy purchased from the grid under the constraint of a limited battery size at each base *** solving the formulated non-convex chance-constrained stochastic optimization problem,a new ambiguity set is built to characterize the uncertainties in the renewable energy and wireless traffic demands according to interval sets of the mean and *** this ambiguity set,the original optimization problem is transformed into a more tractable second-order cone programming problem by exploiting the distributionally robust optimization ***,a low-complexity distributionally robust chance-constrained energy management algo-rithm,which requires only interval sets of the mean and covariance of stochastic parameters,is *** results of extensive simulation are presented to demonstrate that the proposed algorithm outperforms existing methods in terms of the computational complexity,energy cost,and reliability.

关键词： Cellular networks Energy harvesting Energy management Chance-constrained Distributionally robust optimization

来源：评论

学校读者我要写书评

暂无评论

Metaheuristic optimization of Fractional-Order PID Controllers for Quadcopter System 4

Metaheuristic Optimization of Fractional-Order PID Controlle...

引用

4th International Conference on Embedded and Distributed systems, EDiS 2024

作者： Benhammou, Aissa Hartani, Med Amine Kimi, Imade Eddine Tahri Mohamed University Sgre laboratory Bechar Algeria Ahmed draia University Lddi Laboratory Adrar Algeria Ens bechar Dept of physic Bechar Algeria

ISBN: (数字)9798331519872

ISBN: (纸本)9798331519872

The field of robotics has evolved into a highly interdisciplinary domain, encompassing a wide range of challenges that aid humans in several settings, including land, air, sea, and space. The present work offers a comprehensive examination of a quadcopter, specifically emphasising its modelling, control, and optimisation. The notion of stability response is fundamental to the operation of quadcopters and any robotic mechanisms. The present study investigates the possibility of improving quadcopter stability by illustrating the influence of a fractional-order controller-based PID (FOPID) in systems with high sensitivity. The specific methods are used to optimise the five fractional parameters for each controller. This paper presents a comparison of two optimisation techniques, namely Partial Swarm optimization (PSO) and Grey Wolf optimization (GWO), specifically applied to the fractional-order PID controller (FOPID) for the complete quadcopter system. The obtained results indicate that the optimised FOPID controller has significant flexibility in terms of control capabilities compared to classical controllers that are cited in many references, notably decreasing overshoot and enhancing settling and rising times by over 40 % when employing GWO, respecting the same conditions in each algorithm. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

来源：评论

学校读者我要写书评

暂无评论

Hierarchical Controller Synthesis Under Linear Temporal Logic Specifications Using Dynamic Quantization

引用

IEEE/CAA Journal of Automatica Sinica 2024年第10期11卷 2082-2098页

作者： Wei Ren Zhuo-Rui Pan Weiguo Xia Xi-Ming Sun the Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology the School of Control Science and Engineering Dalian University of TechnologyDalian 116024China

Linear temporal logic(LTL)is an intuitive and expressive language to specify complex control tasks,and how to design an efficient control strategy for LTL specification is still a *** this paper,we implement the dynamic quantization technique to propose a novel hierarchical control strategy for nonlinear control systems under LTL *** on the regions of interest involved in the LTL formula,an accepting path is derived first to provide a high-level solution for the controller synthesis ***,we develop a dynamic quantization based approach to verify the realization of the accepting *** realization verification results in the necessity of the controller design and a sequence of quantization regions for the controller ***,the techniques of dynamic quantization and abstraction-based control are combined together to establish the local-to-global control *** abstraction construction and controller design are local and dynamic,thereby resulting in the potential reduction of the computational *** each quantization region can be considered locally and individually,the proposed hierarchical mechanism is more efficient and can solve much larger problems than many existing ***,the proposed control strategy is illustrated via two examples from the path planning and tracking problems of mobile robots.

关键词： Abstraction-based control design dynamic quantization formal methods linear temporal logic(LTL)

来源：评论

学校读者我要写书评

暂无评论

Machine learning parallel system for integrated process-model calibration and accuracy enhancement in sewer-river system

引用

Environmental Science and Ecotechnology 2024年第2期18卷 70-82页

作者： Yundong Li Lina Ma Jingshui Huang Markus Disse Wei Zhan Lipin Li Tianqi Zhang Huihang Sun Yu Tian State Key Laboratory of Urban Water Resource and Environment(SKLUWRE) School of EnvironmentHarbin Institute of TechnologyHarbin150090China Chair of Hydrology and River Basin Management Technical University MunichArcisstrasse 2180333MunichGermany

The process-based water system models have been transitioning from single-functional to integrated multi-objective and multi-functional since the worldwide digital upgrade of urban water system *** proliferation of model complexity results in more significant uncertainty and computational ***,conventional model calibration methods are insufficient in dealing with extensive computational time and limited monitoring *** we introduce a novel machine learning system designed to expedite parameter optimization with limited data and boost efficiency in parameter ***,termed the machine learning parallel system for fast parameter search of integrated process-based models,aims to enhance both the performance and efficiency of the integrated model by ensuring its comprehensiveness,accuracy,and *** was constructed upon the concept of model surrogation t algorithm optimization using Ant Colony optimization(ACO)coupled with Long Short-Term Memory(LSTM).The optimization results of the Integrated sewer network and urban river model demonstrate that the average relative percentage difference of the predicted river pollutant concentrations increases from 1.1 to 6.0,and the average absolute percent bias decreases from 124.3%to 8.8%.The model outputs closely align with the monitoring data,and parameter calibration time is reduced by 89.94%.MLPS enables the efficient optimization of integrated process-based models,facilitating the application of highly precise complex models in environmental *** design of MLPS also presents valuable insights for optimizing complex models in other fields.

关键词： Integrated sewereriver model LSTM ACO SewereWWTPeriver system Water pollution control strategy

来源：评论

学校读者我要写书评

暂无评论

DMGA: A Directional-Mutation Genetic Algorithm for CDMS Problem of Kafka 21

DMGA: A Directional-Mutation Genetic Algorithm for CDMS Prob...

引用

21st International Conference on Networking, Sensing and Control, ICNSC 2024

作者： Ma, Hanbo Ma, Yaofei Yuan, Haitao Wang, Meijia Hu, Jingwei Wang, Yihuan Yang, Hanbo School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Beijing Simulation Center National Key Laboratory of Modeling and Simulation for Complex Systems Beijing China

ISBN: (纸本)9798350365221

With the increasing role of distributed message systems (DMS) represented by Kafka in handling large-scale data streams, it is critical to improve system performance by optimizing configuration parameters in different production environments. Due to the target system possessing numerous configuration parameters and the complex interactions between them, parameter optimization becomes a complex and time-consuming process that relies heavily on human effort and an iterative trial-and-error approach. At present, this type of configuration parameter problem has been classified as the Configuration of Distributed Message systems (CDMS) problem, for which the goal is to obtain the optimal set of parameters for achieving the best performance. In order to deal with this complex problem, an automatic optimization method is proposed in this paper, which combines an automatic script-based deployment and running framework with an improved Genetic Algorithm (GA) in cooperation with the Random Forest (RF) and statistical methods, named the Directional-Mutation Genetic Algorithm (DMGA). The framework and algorithm are designed to find the best configuration efficiently, obtaining optimal parameters accurately without human supervision. Actual results of comparison experiments based on the Kafka system show that the DMGA algorithm significantly improves the data throughput performance of Kafka, and its optimization speed is more efficient than the basic GA, highlighting its potential to quickly optimize Kafka's operational efficiency in different scenarios. © 2024 IEEE.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Continual driver behaviour learning for connected vehicles and intelligent transportation systems: Framework, survey and challenges

引用

Green Energy and Intelligent Transportation 2023年第4期2卷 69-80页

作者： Zirui Li Cheng Gong Yunlong Lin Guopeng Li Xinwei Wang Chao Lu Miao Wang Shanzhi Chen Jianwei Gong Chair of Traffic Process Automation “Friedrich List”Faculty of Transport and Traffic SciencesTU Dresden01069 DresdenGermany School of Mechanical Engineering Beijing Institute of Technology100081 BeijingChina Transport and Planning Civil Engineering and GeosciencesDelft University of Technology2628 CD Delft School of Engineering and Materials Science Queen Mary University of LondonE14NS LondonUK Baidu Inc Beijing 100085China State Key Laboratory of Wireless Mobile Communications China Information and Communication Technology Group Co.Ltd.(CICT)China

modelling,predicting and analysing driver behaviours are essential to advanced driver assistance systems(ADAS)and the comprehensive understanding of complex driving ***,with the development of deep learning(DL),numerous driver behaviour learning(DBL)methods have been proposed and applied in connected vehicles(CV)and intelligent transportation systems(ITS).This study provides a review of DBL,which mainly focuses on typical applications in CV and ***,a comprehensive review of the state-of-the-art DBL is ***,Given the constantly changing nature of real driving scenarios,most existing learning-based models may suffer from the so-called“catastrophic forgetting,”which refers to their inability to perform well in previously learned scenarios after acquiring new *** a solution to the aforementioned issue,this paper presents a framework for continual driver behaviour learning(CDBL)by leveraging continual learning *** proposed CDBL framework is demonstrated to outperform existing methods in behaviour prediction through a case ***,future works,potential challenges and emerging trends in this area are highlighted.

关键词： Driver behaviours Connected vehicles Continual learning Machine learning Intelligent transportation systems

来源：评论

学校读者我要写书评

暂无评论

Balanced operation strategies of district heating systems based on dynamic hydraulic-thermal modeling

引用

Energy and Built Environment 2025年第3期6卷 466-483页

作者： Lin, Xiaojie Zhang, Ning Luo, Zheng Feng, Encheng Zhong, Wei Key Laboratory of Clean Energy and Carbon Neutrality of Zhejiang Province Zhejiang University Zhejiang China Shanghai Institute for Advanced Study Zhejiang University Shanghai China Polytechnic Institute Zhejiang University Zhejiang China Jiaxing Research Institute Zhejiang University Zhejiang China

As the improvement of district heating systems, the fine-tuning of operational equipment has become a promising direction. However, in the practical district heating systems, relying solely on manual control and the existing basic models, the dynamic hydraulic-thermal process is hard to cover. Consequently, the primary side control in the current district heating system mainly results in the over or under-supply of heating substations. This article constructs a dynamic hydraulic-thermal model and performs a balanced operation strategies optimization based on the hydraulic-thermal model. The linearization and iterative optimization process are adopted to simplify the hydraulic and thermal modeling for the single pipe, and the hydraulic and thermal calculation are conducted sequentially. For the primary side network in the various operation conditions, the dynamic hydraulic-thermal model is established. The heating supply imbalance of the primary side return temperatures among different heating substations is defined and optimized based on the dynamic hydraulic-thermal model and the particle swarm optimization algorithm. In the case analysis, the results of heating supply imbalance before and after optimization are 0.81 K and 0.47 K, respectively, with a 42.0 % reduction in heating imbalances after optimization. The proposed method could contribute to the fine-tuning of heating substations and the reduction of energy waste due to the imbalanced heating supply, which is significant for the operation strategies of district heating systems. © 2024

关键词： Iterative methods

来源：评论

学校读者我要写书评

暂无评论

Digital Twins for Wastewater Treatment:A Technical Review

引用

Engineering 2024年第5期36卷 21-35页

作者： Ai-Jie Wang Hewen Li Zhejun He Yu Tao Hongcheng Wang Min Yang Dragan Savic Glen TDaigger Nanqi Ren School of Civil and Environmental Engineering Harbin Institute of Technology(Shenzhen)Shenzhen 518055China State Key Laboratory of Urban Water Resource and Environment Harbin Institute of TechnologyHarbin 150090China Department of Civil and Environmental Engineering Cornell UniversityIthacaNY 14850USA BIOMATH Department of Data Analysis and Mathematical ModellingGhent UniversityGhent 9000Belgium KWR Water Research Institute Nieuwegein 3430 BBNetherlands Centre for Water Systems University of ExeterExeter EX44QFUK Department of Civil and Environmental Engineering University of MichiganAnn ArborMI 48109USA

The digital twins concept enhances modeling and simulation through the integration of real-time data and *** review elucidates the foundational elements of digital twins,covering their concept,entities,domains,and key *** specifically,we investigate the transformative potential of digital twins for the wastewater treatment engineering *** discussion highlights the application of digital twins to wastewater treatment plants(WWTPs)and sewage networks,hardware(i.e.,facilities and pipes,sensors for water quality and activated sludge,hydrodynamics,and power consumption),and software(i.e.,knowledge-based and data-driven models,mechanistic models,hybrid twins,control methods,and the Internet of Things).Furthermore,two cases are provided,followed by an assessment of current challenges in and perspectives on the application of digital twins in *** review serves as an essential primer for wastewater engineers navigating the digital paradigm shift.

关键词： Digital twins Urban water systems Wastewater treatment

来源：评论

学校读者我要写书评

暂无评论

Kinematic Parameter Identification of Industrial Robots Based on an Improved Zebra Algorithm 16th

Kinematic Parameter Identification of Industrial Robots Base...

引用

16th International Conference on modelling, Identification and Control, ICMIC 2024

作者： Zhou, Houchen Gao, Guanbin Wang, Xi Faculty of Mechanical and Electrical Engineering Kunming University of Science and Technology Kunming650500 China Yunnan Key Laboratory of Intelligent Control and Application Kunming650500 China

ISBN: (纸本)9789819617760

Kinematic calibration is one of the main methods to improve the absolute positioning accuracy of industrial robots. Parameter identification is the primary step in determining the calibration effect. However, due to the large number of kinematic parameters of industrial robots and the complex coupling between parameters, the existing parameter identification methods easily fall into local optimal solutions, and it is difficult to obtain accurate kinematic parameters. Therefore, this paper proposes a Particle Swarm Somersault Foraging Zebra optimization Algorithm (PSSFZOA) for kinematic parameter identification of industrial robots. The proposed PSSFZOA introduces the foraging strategy into the Zebra optimization Algorithm (ZOA) and linearizes the kinematic error model so that it does not fall into the local optimum in the later stage of optimization, and improves the population diversity in the early stage. In the first stage of the algorithm, the particle swarm strategy is used to provide local optimal particles, which ensures that the algorithm achieves a balance between global search and local search. It has both the ability of deep search and the diversity of breadth search better to find the best in the complex search space. Simulations are carried out to verify the effectiveness of the method. The results show that compared with the existing Grey Wolf optimization (GWO) and ZOA, the PSSFZOA can avoid falling into local optimum prematurely, accelerate the convergence speed of the algorithm, and improve the absolute positioning accuracy of the industrial robot after parameter identification. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Industrial robots

来源：评论

学校读者我要写书评

暂无评论

Joint Parameter and State-Space modelling of Manufacturing Processes using Gaussian Processes 22

Joint Parameter and State-Space Modelling of Manufacturing P...

引用

22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Kiroriwal, Saksham Pfrommer, Julius Mende, Hendrik Schmitt, Robert H. Beyerer, Jürgen Fraunhofer Institute of Optronics System Technologies and Image Exploitation IOSB Germany Fraunhofer Institute of Production Technology IPT Germany Karlsruhe Institute of Technology Germany WZL: Laboratory for Machine Tools and Production Engineering WZL of RWTH Aachen University Germany

ISBN: (纸本)9798331527471

Manufacturing process optimization is an open question, where Bayesian decision theoretic methods have shown considerable promise. One such is Bayesian optimization, with Gaussian Process (GP) surrogate model. This paper explores Gaussian Processes networks to jointly use parameter and observed state to predict the output(s) of a manufacturing process. The Gaussian process network that represents the paths from parameters to state-space to tasks, provides a methodology to’look inside’ the black-box of complex manufacturing processes. We present a comparative analysis of this method against the multi-task Gaussian processes and single-task counterparts, highlighting the benefits and drawbacks of each in modelling the behavior of such processes. We show the benefits of the proposed approach using numerical experiments. We show that we are able to improve the output prediction by additional sensor observations from inside the process at training time without needing those sensor observations for predicting product quality given the process parameters. © 2024 IEEE.

关键词： Gaussian distribution

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：