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20th IEEE International conference on Environment and Electrical Engineering (EEEIC) / 4th IEEE Industrial and Commercial Power systems Europe conference (I and CPS Europe)

作者： Bertolotti, Valentina Procopio, Renato Rosini, Alessandro Bracco, Stefano Delfino, Federico Soh, Chew Beng Cao, Shuyu Wei, Feng Univ Genoa Dept Elect Elect Telecommun Engn & Naval Architec Genoa Italy Singapore Inst Technol Genoa Italy

ISBN: (数字)9781728174556

ISBN: (纸本)9781728174556

this paper examines Singapore Pulau Ubin microgrid to determine a daily operation management system. Since the grid is an islanded one it lacks the connection to the national network, which would ensure ancillary services such as voltage support or power factor correction. the developed tertiary control system offers a coordinated active-reactive power optimization model for the Pulau Ubin distribution network equipped with an energy storage system, a solar panel field and three biodiesel generators. the aim is to minimize the operation costs and the voltage deviation of the distribution network, managing simultaneously both the active and reactive resources. the results have been validated through a simulation of daily operation carried out by the hour. Upon the successful implementation, this system can serve as a model for the future microgrid embedded in the new SIT campus in Punggol neighbourhood.

关键词： Islanded Microgrid power optimization Pulau Ubin

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Simulation analysis and optimization of thermal performance of crank and connecting rod mechanism of small diesel engine with artificial intelligence 5

Simulation analysis and optimization of thermal performance ...

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5th International conference on Intelligent Computing and Control systems, ICICCS 2021

作者： Li, Kangdiao Xiao, Caiyuan He, Lvhang Yi, Bolong Zhu, Libin Zhou, Yuzhao Key Laboratory of Hunan Province for Efficient Power System and Intelligent Manufacturing Shaoyang Hunan422000 China College of Mechanical and Energy Engineering Shaoyang University Shaoyang Hunan422000 China

ISBN: (纸本)9781665412728

Simulation analysis and optimization of thermal performance of crank and connecting rod mechanism of small diesel engine with artificial intelligence is studied in this paper. Artificial neural network is responsible for knowledge acquisition and empirical thinking., artificial intelligence is responsible for logical thinking, and knowledge base is also responsible for the function of knowledge memory, and their joint work can improve the accuracy of the model. the excellent performance parameters can be then converted to breaking design machine by general computer programming, hence, the modeling is applied into the design. the experiment on the proposed framework proves the efficiency. © 2021 IEEE.

关键词： Diesel engines

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Research on global energy optimization of central air conditioning system based on particle swarm optimizer with penalty functions

Research on global energy optimization of central air condit...

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Youth Academic Annual conference of Chinese Association of Automation (YAC)

作者： Qi Li Yixin Su Danhong Zhang Chenyu Liu Huajun Zhang Zijian Yan School of Automation Wuhan University of Technology Wuhan China

ISBN: (纸本)9781665465373

In modern large buildings, a significant portion of the building’s energy use is used by the central air conditioning system. this study aims to determine how much energy the central air conditioning system uses during operation by modifying the operating parameters of each main piece of equipment. First, the energy consumption models of each major equipment are established separately, so as to establish a global energy consumption model. For the problem of high coupling among the equipment, various nonlinear constraints are introduced. An updated particle swarm algorithm is used to find the operating parameters that make the central air conditioning system’s operation globally optimal in order to solve the nonlinear constraint optimization problem. Compared with the ordinary gradient descent algorithm, the particle swarm algorithm finds the global optimal solution more easily. According to simulations, the optimization algorithm can reduce energy use by 20% to 30%.

关键词： Couplings Constraint optimization Energy consumption Atmospheric modeling Buildings Central air conditioning Search problems

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Research on Safety modeling and Analysis to the Task Process of Airborne Weather system 20

Research on Safety Modeling and Analysis to the Task Process...

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20th IEEE International conference on Software Quality, Reliability, and Security (QRS)

作者： Niu, Haotian Ma, Cunbao Han, Pei Li, Siyuan Ma, Qi Zhang, Shenghui Northwestern Polytech Univ Sch Aeronaut Xian Peoples R China China Elect Technol Grp Ctr Inst 20 Commun Div Xian Peoples R China AVIC Qianshan Avion Co Ltd Tech Ctr Xian Peoples R China

ISBN: (纸本)9781728189154

Airborne Weather Radar (WXR) is an important system for civil aircraft to deal with hazardous weather conditions. Numbers of potential hazardous factors exist in task process. In this paper, a model-based method is proposed to analyze the accident occurrence mechanism and system safety while considering the interaction between social-technical elements. the hybrid model consists of five parts, including social-organizational risk model, human error model, failure model of system, maintenance error model, and failure model of WXR task process. Moreover, different modeling technologies are adopted to construct these models. then, the hybrid model is utilized to identify potential hazardous factors and achieve safety analysis for the social-technical system in both qualitative and quantitative way. Additionally, potential hazardous causes are sorted according to influence degrees. the analysis results indicate that the method can achieve safety analysis for the task process, and provide technical support for the safety design of airborne WXR system.

关键词： airborne weather radar system process safety social-technical system safety modeling and analysis hybrid model

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the Study of the Possibilities of Constructing Cognitive Models of Complex systems as a Result of the Analysis of Time Series of a Limited Number of Factors on the Example of Financial Markets 20th

The Study of the Possibilities of Constructing Cognitive Mod...

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20th IFAC conference on Technology, Culture, and International Stability (TECIS)

作者： Chernov, Igor, V Cherenkov, Ivan, V Feyzov, Vadim R. Russian Acad Sci VA Trapeznikov Inst Control Sci Moscow Russia

the complexity of problems related to the formation of cognitive models of complex systems based on methods of econometric analysis of available time series of domain parameters is considered. An approach is proposed to solve the problem of representing a complex system in the form of an understandable and practical model that includes a limited number of factors, but as adequately as possible reflects the dynamic processes occurring in this system. An example of the application of the proposed approach is considered, exploring the possibilities of improving the efficiency of the functioning of financial markets. the vector autoregression model, which is a model of the dynamics of several time series, is chosen as the basis for the formation of the model. Options for improving the model by adding virtual factors and cointegrating relations are proposed, and the results of the study of the developed model are also presented. Copyright (C) 2021 the Authors.

关键词： cognitive modeling financial market economic security complex system forecasting time series

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Online Conflict-Free Scheduling of Fleets of Autonomous Mobile Robots

Online Conflict-Free Scheduling of Fleets of Autonomous Mobi...

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IEEE International conference on Automation Science and Engineering (CASE)

作者： Francesco Popolizio Martina Vinetti Alvin Combrink Sabino Francesco Roselli Maria Pia Fanti Martin Fabian Department of Electrical Engineering Division of Systems and Control Chalmers University of Technology Göteborg Sweden Department of Electrical and Information Engineering Polytechnic of Bari Bari Italy

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

this work presents a Fleet Manager for a fleet of Autonomous Mobile Robots (AMRs) that perform material handling tasks in a shared environment. the Fleet Manager assigns AMRs to newly released tasks, computes paths for them to travel to the task’s locations, and schedules their travel along the computed paths so that conflicts with other AMRs are avoided. the objective is for each AMR to complete its task as quickly as possible, to then be assigned a new *** Fleet Manager works online, assigning a released task to the AMR closest to the task’s location, and then computing the path and schedule to fit in with the already assigned and executing AMRs. Conflicts occur when, in order to reach their targets, AMRs would have to simultaneously occupy the same space. Resolving this is done by appropriate scheduling, or by moving idle AMRs out of the way. For fleet management to be practicable, the computation time for assigning an AMR to a task and computing its path and schedule must be negligible compared to other system *** were conducted to evaluate the performance of the Fleet Manager on a number of benchmark problem instances, counting up to hundreds of AMRs. the results show that the presented Fleet Manager can handle these systems quickly enough to be practically useful in real industrial scenarios.

关键词： Schedules Job shop scheduling Processor scheduling Benchmark testing throughput Real-time systems Path planning Mobile robots optimization Autonomous robots

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K-Means Clustering via a Nonconvex optimization Approach 20th

K-Means Clustering via a Nonconvex Optimization Approach

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20th International conference on Mathematical optimization theory and Operations Research, MOTOR 2021

作者： Gruzdeva, Tatiana V. Ushakov, Anton V. Matrosov Institute for System Dynamics and Control Theory of SB RAS 134 Lermontov Street Irkutsk664033 Russia

ISBN: (纸本)9783030778750

Clustering is one of the basic tasks in machine learning and data mining. Euclidean minimum-sum-of-squares clustering problem is probably the most common clustering model. It consists in finding k cluster centers or representatives so as the sum of squared Euclidean distances from a set of points and their closest centers is minimized. the problem is known to be nonconvex and NP-hard even in the planner case. In this paper, we propose a new DC programming approach to the problem. First, we cast the original nonconvex problem as a continuous optimization problem with the objective function represented as a DC function. We then devise a solution algorithm, resting upon the global optimality conditions and global search scheme for DC minimization problems proposed by A.S. Strekalovsky. We implement the developed algorithm and compare it with k-means clustering algorithms on generated datasets. © 2021, Springer Nature Switzerland AG.

关键词： K-means clustering

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Fractional-order model reference adaptive control of a multi-source renewable energy system with coupled DC/DC converters power compensation

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ENERGY systemS-optimization modeling SIMULATION AND ECONOMIC ASPECTS 2020年第2期11卷 315-355页

作者： Djebbri, Sihem Ladaci, Samir Metatla, Abderezzak Balaska, Hanane Univ 20th August 1955 Elect Engn Dept Lab Genie Mecan & Mat Skikda 21000 Algeria Natl Polytech Sch Constantine EEA Dept Nouvelle ville Ali Mendjeli Constantine 25100 Algeria Univ Mentouri Bros SP Lab Lab Constantine 25000 Algeria Univ 20th August 1955 Mech Engn Dept Lab Genie Mecan & Mat Skikda 21000 Algeria Univ Larbi Ben MHidi Dept Sci & Technol LGEA Lab Oum El Bouaghi 04000 Algeria

We propose a supervision strategy based on a fractional order model reference adaptive control (FO-MRAC) design for the control of electrical energy transfers in a multi-source renewable energy system. We consider a two sources system (photo-voltaic and lead-acid battery bank) with a specific zero voltage switch full-bridge isolated buck DC/DC power converter and the load which is supposed to be resistive. the global energy system involving coupled DC/DC converters on a DC bus is accurately modelized in the state space domain. then, a fractional order MRAC control law is designed in order to stabilize the system's current and voltage. We show by means of numerical simulation tests that the proposed FO-MRAC control is very efficient and robust even in presence of renewable sources fluctuations and load variations.

关键词： Fractional-order adaptive control FOMRAC Fractional order integral Multi-source renewable energy system DC DC power converter

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Machine Learning Applications in Short-term Financial Forecasting: A Comparative Analysis with Hybrid Model

Machine Learning Applications in Short-term Financial Foreca...

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International conference on Contemporary Computing and Informatics (IC3I)

作者： Kamaljeet Kaur Mamta Gupta Dibyahash Bordoloi Pradeepta Kumar Sarangi Srikanta Kumar Mohapatra Alok Kumar Agrawal M M Institute of Management Maharishi Markandeshwar (Deemed to be university) Mullana-Ambala Haryana India Panipat Institute of Engineering and Technology Samalkha Haryana India Department of CSE Graphic Era Hill University Graphic Era Deemed to be University Dehradun Uttarakhand India Chitkara University School of Engineering & Technology Chitkara University Himachal Pradesh India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

Financial analysis and trading are very crucial in any economy. It holds a significant importance to generate income and reducing income equality, especially in developing countries where inequality and employment are major concerns. Forex analysis deals with the currency exchange and plays a major role in world economy. Accurate prediction of currency market is almost impossible as there are many unpredictable factors may instantly come to play and greatly affect the market scenario. Hence, long term predictions may not be very successful however, short term predictions or very short-term prediction may be accurate up to some extent. this work tries to predict the next day currency exchange rate (US Dollar to Indian Rupees) using machine learning models. three machine learning models such as ANN-PSO, RNN and LSTM have been implemented to predict the next day currency exchange rate. the data set used in this work is the daily trading data downloaded from the *** for the period 1st January 2020 to 20th May 2024. Using the close price of these values the models were trained and the value for the day 21st May 2024 has been predicted. the predicted value for 21st May is $83.39,83.27$ and 83.47 by RNN, LSTM and ANN-PSO models respectively. Comparing this with the actual value of 21st May 2024, the accuracy thus calculated for the models are $\mathbf{9 9. 8 6 \%}, \mathbf{9 9. 9 8 \%}$ and $\mathbf{9 9. 7 8 \%}$ by RNN, LSTM and ANN-PSO models respectively.

关键词： Exchange rates Accuracy Biological system modeling Computational modeling Machine learning Predictive models Informatics Forecasting Currencies Long short term memory

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A combined PV-wind energy system for an energy saving greenhouse

A combined PV-wind energy system for an energy saving greenh...

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20th IEEE International conference on Environment and Electrical Engineering (EEEIC) / 4th IEEE Industrial and Commercial Power systems Europe conference (I and CPS Europe)

作者： Riahi, Jamel Vergura, Silvano Mezghani, Dhafer Mami, Abdelkader Univ Tunis Fac Sci Tunis UR LAPER Tunis Tunisia Polytech Univ Bari Dept Elect & Informat Engn Bari Italy

ISBN: (纸本)9781728174556

this paper presents the optimization and simulation of a hybrid power system composed of two renewable energy sources to supply the actuators of an agricultural greenhouse. the first system is a PhotoVoltaic (PV) generator connected to a DC/AC inverter and the second system is a wind turbine connected to a Permanent Magnet Synchronous Generator (PMSG). A Maximum Power Point Tracking (MPPT) control based on fuzzy logic is used to drive a SEPIC converter to feed the maximum power to the agricultural greenhouse. the simulation and validation of the system is carried out in Matlab/Simulink environment. the results show that the proposed system provides an efficient solution to control the microclimate of the agricultural greenhouse in different periods of the year.

关键词： Hybrid systems PV system Wind plant Converter SEPIC Greenhouse Fuzzy logic controller Matlab Simulink

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