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检索条件"任意字段=International Conference on Complex Systems: Control and Modeling Problems"

共 12248 条记录，以下是1261-1270 订阅

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An Integrated Online-Offline Hybrid Particle Swarm Optimization Framework for Medium Scale Expensive problems*

An Integrated Online-Offline Hybrid Particle Swarm Optimizat...

引用

Data-driven Optimization of complex systems (DOCS), international conference on

作者： Hanyu Hu Jian Wang Xiaodong Huang Sergey V. Ablameyko College of Computer Science and Technology China University of Petroleum (East China) Qingdao China College of science) China University of Petroleum (East China) Qingdao China College of Control Science and Engineering China University of Petroleum (East China) Qingdao China Faculty of Applied Mathematics and Computer Science Belarusian State University Minsk Belarus

ISBN: (数字)9798350377842

ISBN: (纸本)9798350377859

Real-world optimization problems often involve computationally expensive evaluations, making efficient optimization crucial. To address medium-scale expensive optimization problems, this paper proposes and investigates an Integrated Online-Offline Hybrid Particle Swarm Optimization Framework (IOOPSOF). The framework integrates concepts from active learning and ensemble learning, iteratively querying the most uncertain and highest-precision solutions to achieve efficient utilization of evaluation resources. IOOPSOF employs two distinct sample selection criteria, with offline optimization for exploration and online optimization for exploitation. The effectiveness of the proposed method is validated through experiments on a series of low to medium-dimensional benchmark functions and the operational parameter optimization of Enhanced Geothermal systems (EGS). Results demonstrate that IOOPSOF significantly outperforms existing methods, achieving global optimum (0) on most benchmark functions and showing superior performance over single surrogate-assisted evolutionary algorithms (SAEAs) on real-world problems, thereby showcasing its exceptional potential for solving expensive optimization problems.

关键词： Decision making Benchmark testing Computational efficiency Ensemble learning Particle swarm optimization complex systems Optimization Standards

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Decentralized controller Design and Gain Tuning Approach for MIMO systems: Application to Reel-to-Reel systems

Decentralized Controller Design and Gain Tuning Approach for...

引用

international conference on Mechatronics (ICM)

作者： Aakash Dewangan V. Kartik Mechanical Engineering Department Indian Institute of Technology Bombay Mumbai India

ISBN: (数字)9798331533892

ISBN: (纸本)9798331533908

Multi-input multi-output (MIMO) control systems are common in many industrial applications, such as reel-to-reel (R2R) systems, process control in distillation columns, robotic manipulators, and flight control. The coupling between plant inputs and outputs makes controller design challenging, especially when selecting controller gains in transfer function-based approach. This paper proposes a simple yet practical method for designing the controller using a decentralized approach based on transfer functions, along with an intuitive gain-tuning procedure. Unlike state-of-the-art methods, this approach does not require solving complex optimization problems. It is also generalizable to any MIMO control system. The controller design approach simplifies the MIMO system by shaping the open-loop transfer function into a triangular form, allowing it to be treated as a set of individual SISO systems. Each SISO system is influenced by a specific level of internal disturbance. These disturbances are associated with the dynamics of the actuators controlling the control variables, and therefore can be modeled based on the knowledge of the actuator dynamics. This makes controller design and gain tuning simpler compared to the complex algorithms used in the literature. The effectiveness of the proposed approach is demonstrated by its implementation on a $2\times 2$ R2R system hardware. Finally, the stability and robustness of the designed control system are experimentally assessed and various stability margins are obtained.

关键词： Actuators Mechatronics Service robots Transfer functions Process control Stability analysis MIMO Robustness Tuning Optimization

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SiC JFET Template Model for Extremely High-Temperatures

SiC JFET Template Model for Extremely High-Temperatures

引用

international conference on Actual problems of Electron Devices Engineering, (APEDE)

作者： Alexandr M. Pilipenko Dmitriy V. Kleimenkin Vadim N. Biryukov Anna V. Bugakova Department of Fundamentals of Radio Engineering Southern Federal University Taganrog Russia Department of Scientific Research Department of Information Systems and Radio Engineering Don State Technical University Rostov-on-Don Russia

ISBN: (数字)9798350393316

ISBN: (纸本)9798350393323

The paper proposes a compact model of a silicon-carbide (SiC) field-effect transistor with control p-n junction (JFET) whose parameters are determined by measurements. The model is developed using the template modeling method, in which constant parameters of the model are replaced by fractional-rational functions (Padé approximation), allowing to describe more accurately the physical processes in the electronic component without violating the nature of their change. The demonstrated SiC JFET model is formulated as a function of both the fundamental process parameters that control the electrical behavior of the device (e.g., threshold voltage) and the geometric layout parameters associated with the device (e.g., device length and width), providing a rational basis for statistical modeling of process variation effects.

关键词： Silicon carbide Layout Process control Electronic components Threshold voltage JFETs Transistors Integrated circuit modeling Electron devices P-n junctions

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Static Output Feedback control Synthesis for Positive Polynomial Fuzzy systems with time delay 9

Static Output Feedback Control Synthesis for Positive Polyno...

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9th international conference on systems and control (ICSC)

作者： Messaoudi, A. Ammar, I. Iben Gassara, H. El Hajjaji, A. Univ Sfax Lab Sci & Tech Automat Control & Comp Engn Lab ST PB 1173 Sfax 3038 Tunisia Univ Picardie Jules Verne Modeling Informat & Syst Lab MIS UFR Sci 33 Rue St Leu F-80000 Amiens France

ISBN: (纸本)9781665407823

This paper presents the static output feedback control synthesis problem for a class of positive polynomial fuzzy systems with time delay using a sum of squares (SOS) approach. To study the considered analysis and design problems, the polynomial Lyapunov-Krasovskii function is proposed. Based on The sum of squares technique, the polynomial conditions can be directly solved. Finally, a simulation example is given to testify the validity of the analysis result.

关键词： Positive polynomial fuzzy model time delay Static Output Feedback control Sum of squares (SOS)

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Technology of hardware and software modeling of spacecraft attitude sensors based on STM32 microcontrollers 4

Technology of hardware and software modeling of spacecraft a...

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4th international conference on control in Technical systems, CTS 2021

作者： Kulakov, Aleksandr Yu. Smirnov, Aleksandr V. St. Petersburg Federal Research Center of the Russian Academy of Sciences St. Petersburg Russia

ISBN: (纸本)9781665424547

Currently, the concept of hardware and software modeling of complex technical objects (CTO) has received rapid development, including in the space industry. The main feature of such objects is the presence of real-time control systems with a complex and sometimes heterogeneous structure. The concept of "X-In-the-Loop" has gained great popularity in foreign literature when considering modeling of CTO. Among the specialized software (SW) for modeling spacecraft (SC), it is worth highlighting open source SW that has sufficient documentation to understand their work and an active community on the Internet. This report proposes a hardware-software modeling technology based on Project 42 (SW for modeling of SC) and microcontroller (MC) STM32. To work with MC STM32 within the framework of this technology, the integrated development environment IAR Embedded Workbench is used. © 2021 IEEE.

关键词： Real time control

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Determination of Chemical Mixture Viscosity by Means of Machine Learning Methods

Determination of Chemical Mixture Viscosity by Means of Mach...

引用

international Russian Smart Industry conference (SmartIndustryCon)

作者： Tatyana V. Lapteva Sergey A. Laptev Yuri S. Chistov Information Technology and Information Systems Department Kazan State Power Engineering University Kazan Russian Federation Power Engineering Department Kazan State Power Engineering University Kazan Russian Federation Systems Engineering Department Kazan National Research Technological University Kazan Russian Federation

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

Mathematical modeling of petrochemical, oil refining and oil treatment processes is an integral part of the systems of pre-project analysis of newly created, operability of operating plants, as well as systems of automated control of technological processes. Chemical-technological processes are multi-level complex systems, the hierarchy of which varies depending on the process in progress. Each of the hierarchy levels is represented by a system of equations of varying complexity, which is further reduced to a system of nonlinear equations including transcendental functions. The solution of such systems requires considerable time even when using modern computational methods, which is unacceptable, especially when used in advanced process control systems. In this paper we propose a method of calculating the viscosity of a broad fraction of hydrocarbons based on the use of machine learning models, namely neural networks. In order to accelerate training and obtain the result, the decomposition of the initial problem into a set of tasks, less parametric, which facilitates the process of training the model. Thanks to this decomposition, for a number of regions of the feature space, there is no need to calculate viscosity. To solve the problem of calculating the viscosity of a chemical mixture, a program complex was created to ensure the interaction of trained neural networks.

关键词： Viscosity Training Oils Neural networks Process control Machine learning Hydrocarbons Mathematical models Iterative methods Chemicals

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Macroscopic Description of Structured Heterogeneous Online Social systems with Dynamical Opinions

Macroscopic Description of Structured Heterogeneous Online S...

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international conference on control systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA)

作者： Vladislav N. Gezha Ivan V. Kozitsin Phystech School of Applied Mathematics and Informatics Moscow Institute of Physics and Technology Dolgorpudny Russia Laboratory of Active Systems Institute of Control Sciences of RAS Moscow Russia

ISBN: (数字)9798331532178

ISBN: (纸本)9798331532185

Mean-field approximation techniques are widely used to model dynamics of large complex stochastic systems, which are extremely difficult to describe using precise equations. However, in the context of the modelling of social systems, such an approach may lead to inaccurate solutions, as real-life social networks feature structurality whereby individuals form their ego-graphs not at random. Resulting social networks are modular and tend to include dense groups of vertices-communities-whose presence may seriously affect various processes in networks, including information dissemination, innovation diffusion, and opinion formation. Besides this, communication networks that establish on social media platforms display substantial activity heterogeneity and are subject to individuals' cognitive biases and the moderation by personalization systems. In this vein, naive aggregation techniques may fail to cope. This paper considers a model that describes how a structured population of individuals update their opinions following pairwise stochastic interactions. For this model we develop a mean-field approximation that accounts for all the roadblock factors mentioned above and investigates the key properties of the resulting master equation.

关键词： Technological innovation Social networking (online) Stochastic systems Stochastic processes Process control control systems Mathematical models Energy efficiency Numerical models Context modeling

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Data-Driven Dynamic modeling and Fault Diagnosis of Dimethyl Oxalate Industrial Production Process

Data-Driven Dynamic Modeling and Fault Diagnosis of Dimethyl...

引用

Data-driven Optimization of complex systems (DOCS), international conference on

作者： Jingxuan Zhang Guo Yu Cuimei Bo Jun Li Nanjing Tech University Nanjing China

ISBN: (数字)9798350377842

ISBN: (纸本)9798350377859

Ethylene glycol (EG) is an indispensable substance in the chemical industry and polyester fiber supply chain. The synthesis of dimethyl oxalate (DMO) by carbon monoxide gas-phase catalytic coupling is a key step in the coal-based syngas to ethylene glycol process route. The strong coupling between the reaction unit and the feedstock regeneration unit, as well as the risk of feedstock gas explosion, poses a great challenge to the stability control and safety of the dimethyl oxalate production process. In this paper, the dimethyl oxalate production process is studied from three aspects: steady-state modeling, dynamic modeling and fault simulation. First, the dimethyl oxalate pro-duction process was comprehensively modeled using Aspen Plus software. Second, a dynamic model was constructed on the basis of the steady-state model to fit the actual production process. Finally, deep learning algorithms were combined with dynamic simulation techniques. Using the fault scenarios and data in the dynamic model, the T-DOAE algorithm is used to study the fault detection in the production process of dimethyl oxalate, which is of great significance to ensure the safe and stable operation of the gas-phase coupling process of dimethyl oxalate production in the process of coal chemical industry.

关键词： Couplings Heuristic algorithms Fault detection Software algorithms Process control Production Software Data models Steady-state Safety

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Parallel control for Robust Optimal Tracking via Adaptive Dynamic Programming

Parallel Control for Robust Optimal Tracking via Adaptive Dy...

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complex systems and Intelligent Science (CSIS-IAC), international Annual conference on

作者： Shanshan Jiao Qinglai Wei Institute of Systems Engineering Macau University of Science and Technology Macau China

This paper attempts to develop a novel robust optimal tracking control method for continuous-time uncertain nonlinear systems via adaptive dynamic programming (ADP). First, a control system for the actual system is established based on the parallel control scheme, so that the general nonlinear system can be transformed into an affine system to introduce the optimal tracking control problem by defining an augmented vector. Then, the main objective of this paper is to investigate the relationship between the solutions of the optimal control problems for the uncertain system and the nominal system. Furthermore, critic neural networks (NNs) are utilized to design the virtual control law to achieve the proposed robust optimal control online. Finally, simulation experiments validate the effectiveness of the proposed method.

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Representation of the Mechanism for Constructing an Integrated Method of Solving a Diagnostic Problem and Results of Its Work 3

Representation of the Mechanism for Constructing an Integrat...

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3rd international conference on control systems, Mathematical modeling, Automation and Energy Efficiency, SUMMA 2021

作者： Rumovskaya, Sophiya Kaliningrad Br. of the Fed. Res. Ctr. 'Comp. Science and Control' of the Russian Academy of Sciences Kaliningrad Russia

ISBN: (纸本)9781665439817

In the paper, we present the results of the development of the language of schemes of role-based visual relations for representation of 'an integrated method of solving a diagnostic problem' and the heuristic mechanism of solving problems by dynamically restructuring the whole into a decomposition of a related task. © 2021 IEEE.

关键词： Heuristic methods

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