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

共 12149 条记录，以下是171-180 订阅

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Neural Network modeling and PID control for 3- DOF Horizontal Stabilization Platform 13

Neural Network Modeling and PID Control for 3- DOF Horizonta...

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Joint 13th international conference on Soft Computing and Intelligent systems and 25th international Symposium on Advanced Intelligent systems, SCIS and ISIS 2024

作者： Kim, Junhyeong Kim, Dong Hun Kyungnam University Dept. Mechatronics Engineering Changwon Korea Republic of

ISBN: (纸本)9798350373332

This paper proposes a method to implement an 3-dof stabilization device by combining a neural network with a PID controller. First, hardware was designed based on the Inverted Delta Robot structure. This platform, equipped with three servo motors and an IMU sensor, is suggested as a real-time stabilization platform. Second, using servo motors with limited angular movement, real-time data on Roll and Pitch angles were collected. Third, the collected data were preprocessed, and a neural network model with the ReLU function as the activation function was trained. Fourth, the trained model was used to output stabilization error values to the PID controller, maintaining the device's balance. This study demonstrates the potential of combining neural networks with PID controllers for stabilization devices. Future research will require experiments in various industrial environments, sensor integration, and neural network optimization. © 2024 IEEE.

关键词： Three term control systems

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Multi-agent systems in the Task of modeling Medical Organizations 26

Multi-agent Systems in the Task of Modeling Medical Organiza...

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26th international conference on Soft Computing and Measurements, SCM 2023

作者： Eirich, Michael Oliseenko, Valerii D. St. Petersburg State University Laboratory of Theoretical and Interdisciplinary Problems of Informatics St. Petersburg Federal Research Center The Russian Academy of Sciences Mathematics and Mechanics Faculty St. Petersburg Russia Laboratory of Theoretical and Interdisciplinary Problems of Informatics St. Petersburg Federal Research Center The Russian Academy of Sciences St. Petersburg Russia

ISBN: (纸本)9798350322484

The issue of creating a system for modeling the processes taking place inside medical organizations is very complex and time-consuming. Multi-agent systems (MAS) based on fuzzy rules are often used to solve it. With MAS you can simulate the flow of patients, the work of staff and specialized equipment, but the creation of such systems requires special knowledge and skills. The result of this work is an algorithm for the step-by-step construction of such systems: from the technical formulation of the problem to the choice of the software environment. © 2023 IEEE.

关键词： Soft computing

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Fast identification method of redundant constraints based on variable load 9

Fast identification method of redundant constraints based on...

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9th international conference on Energy Materials and Electrical Engineering, ICEMEE 2023

作者： Yang, Yinguo Lu, Qiuyu Lin, Xu Xie, Pingping Liu, Yang Dispatching Control Center of Guangdong Power Grid Co. Ltd Guangzhou510000 China

ISBN: (纸本)9781510672765

In the clearing process of the provincial/regional electricity spot market, large-scale zero to one decision variables and complex constraints greatly affect the computational efficiency of solving unit commitment problems. However, among all constraints considered in security-constrained unit commitment, some redundant ones are not effective. If these constraints are identified and removed from the optimization model, the calculation efficiency can be greatly improved without changing the optimal solution of the original problem. Therefore, firstly, the general idea of rapid identification of redundant constraints based on variable load is proposed. Secondly, on the basis of the traditional security-constrained unit commitment model of the electricity spot market, a mathematical model of redundancy constraint identification is proposed, and the specific processing method of redundancy constraint identification is proposed as well. Finally, the correctness and effectiveness of the proposed method are verified by an example. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Mathematical modeling Mathematical optimization systems modeling Computer programming Medium wave Power grids Decision making Polymerization Safety Tolerancing

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Model-Free Dynamic control of Five-bar Mechanism via Subchain Assembly and Reinforcement Learning 12

Model-Free Dynamic Control of Five-bar Mechanism via Subchai...

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12th RSI international conference on Robotics and Mechatronics, ICRoM 2024

作者： Sedghi, Soheil Tale Masouleh, Mehdi Kalhor, Ahmad School of Electrical and Computer Engineering University of Tehran Human and Robot Interaction Laboratory Tehran Iran

ISBN: (纸本)9798331529734

Parallel robots are versatile but challenging to control due to their complex dynamics and the need for precise modeling. This research presents a novel approach to modular control of parallel robots, utilizing reinforcement learning to dynamically assemble and control complex arbitrary systems. By treating each sub chain of a parallel robot as an individual agent, the proposed method offers a flexible and adaptable framework for various control tasks. The study compares the learning performance of different RL algorithms and proposed decision modeling on the tracking control of a five-bar robot with a 55 cm link length, aiming to achieve an error of less than 5 cm in the PyBullet simulator. In single-agent reinforcement learning, three algorithms (DDPG, PPO, and SAC) were employed, with PPO and SAC effectively solving the problem. In multi-agent reinforcement learning, two algorithms (FACMAC and MAPPO) were utilized. While MAPPO successfully learned the problem, FACMAC exhibited difficulties in grasping the problem. The results obtained from comparing the proposed RL algorithms indicated that single-agent RL learns the control problem better and faster than multi-agent reinforcement learning. In short, the paper focuses on formulating an RL solution which can effectively control parallel robots and can potentially be used for pre-training subchains. © 2024 IEEE.

关键词： Reinforcement learning

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Numerical modeling and Some Optimal control problems of Dynamic systems Describing Contact problems with Friction in Elasticity 27th

Numerical Modeling and Some Optimal Control Problems of Dyna...

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27th international conference on Difference Equations and Applications (ICDEA)

作者： Pop, Nicolae Sireteanu, Tudor Vladareanu, Luige Iliescu, Mihaiela Mitu, Ana-Maria Maxim, Vicentiu Marius Romanian Acad Inst Solid Mech Constantin Mille 15 Bucharest 10141 Romania

ISBN: (纸本)9783031510519;9783031510496;9783031510489

The purpose of the article is to make use of difference equations to solve the dynamic visco-elastic contact problems with friction. First of all, we propose the discretization in space and time of the equilibrium equations and the use of regularization methods to approximate the non-differentiable terms that model the contact friction, Coulomb type. For the discretization in space of the problem of dynamic elastic contact with friction, the finite element method is used and a system of ordinary differential equations of the second order will result, which will be solved using the finite difference method, the Newmark method and the Newton-Raphson iterative method of solving the linearized dynamic system. The model predictive control (MPC) and the linear quadratic regulator (LQR), described by the linear discrete-time difference equations derived from the system of nonlinear differential equations, have been used to solve some optimal control problems. This problem is of great importance in engineering applications, for example for the control of deformations, velocities and accelerations in areas of interest, and vibration mitigation. Areas of interest could be: the tool tip of a machine tool or the end efector of a robotic arm with links and joints etc.

关键词： Finite differences Discrete-time difference equations Nonlinear system Newton-Raphson iterative method Model predictive control Linear quadratic regulator Constrained control Dynamic systems Unilateral dry contact problem Finite element method Coulomb law

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Location Optimization of Automated Warehouse Based on Swarm Intelligence Optimization Algorithm 13

Location Optimization of Automated Warehouse Based on Swarm ...

引用

13th international conference on Logistics and systems Engineering

作者： Jiajing, Wang Di, Liu Yingyuan, Zeng College of Information and Control Engineering Xi’an University of Architecture and Technology Xi’an China

ISBN: (纸本)9781713896708

Aiming at the problem of location allocation in an intelligent warehouse, this paper presents a method for solving complex multi-objective optimization problems by using the swarm intelligence optimization algorithm. Firstly, considering the factors such as stability and activity-based cost, a multi-constrained optimal allocation model of goods location is constructed. Secondly, considering the influence of individual domains, population topology, and individual learning behavior on search in the swarm intelligence optimization algorithm, a metaheuristic optimization algorithm based on swarm intelligence with social network behavioralled Social Network-based Swarm Optimization (SNSO) algorithm is constructed. Finally, a case study of an automated warehouse is presented to show that the proposed strategy can solve such problems steadily. © 2024 Proceedings of the 13th international conference on Logistics and systems Engineering. All rights reserved.

关键词： Swarm intelligence

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Solving Multi-capacitated Facility Location Problem in Traffic control systems Using Lagrangian Relaxation and Decomposition Approach 7th

Solving Multi-capacitated Facility Location Problem in Traff...

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7th international conference on Logistics Operations Management (GOL)

作者： El Amrani, Mohammed Bouanane, Khaoula Abba, Khalil Benadada, Youssef Mohammed V Univ Rabat Fac Sci Algorithms Networks Intelligent Syst & Software E Rabat Morocco Ecole Marocaine Ingn Polytech Smart Lab Rabat Morocco Mohammed V Univ Rabat ENSIAS Rabat IT Ctr Smart Syst Lab Rabat Morocco

ISBN: (纸本)9783031686337;9783031686344

The Budget-Constraint Multi-Capacitated Location Problem represents a generalized extension of the classical p-median location problems. It involves the allocation of predetermined capacity levels constraints to each facility while efficiently assigning customers within a network to minimize total connection costs. In this study, we explore the application of this model in the domain of road traffic regulation to optimize network installation and determine the appropriate server configurations required for processing data collected from sensors. In the second section of this paper, we address the problem through a new approach rooted in Lagrangian relaxation and decomposition. This innovative approach facilitates parallel computing, resulting in a notable reduction in execution time. The resolution of this complex problem encompasses two key stages: the calculation of Lagrange multipliers and the implementation of a heuristic method to ensure solution feasibility. Ultimately, we present computational results obtained by solving new instances derived from p-median problems found in the existing literature. Our research contributes to addressing real-world traffic management challenges by optimizing facility placement and resource allocation, with practical implications for improving traffic control systems.

关键词： Facility Location Lagrangian Relaxation SubGradient Road Traffic control

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Analysis of Methods of Augmentation of Images of the Branding of Cast Billet at A. A. Ugarov Oskol Electrometallurgical Plant 5

Analysis of Methods of Augmentation of Images of the Brandin...

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5th international conference on control systems, Mathematical modeling, Automation and Energy Efficiency, SUMMA 2023

作者： Poleshchenko, Dmitriy Zorin, Ivan Automated and Information Control Systems Department Stary Oskol Russia

ISBN: (纸本)9798350309126

The paper deals with the procedure of increasing the training sample size using augmentation methods. The paper considers the main methods of image augmentation, selects the most suitable ones for solving the presented class of problems, and approbation of these methods with testing on the deep learning neural network Faster R-CNN. It is shown that the use of augmentation methods to increase the image base allows to raise the quality of training of the neural network by 1%. It is also found that the type of augmentation should correlate with the prevailing type of disturbance affecting the image quality. © 2023 IEEE.

关键词： Deep learning

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Nonlinear control Law Design for Overhead Crane to Supress Load Oscillations 5

Nonlinear Control Law Design for Overhead Crane to Supress L...

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5th international conference on control systems, Mathematical modeling, Automation and Energy Efficiency, SUMMA 2023

作者： Petrov, Vladislav Glushchenko, Anton Vorobyev, Vladislav Lastochkin, Konstantin NUST MISIS Department of Automated and Information Control Systems N.a. Y.I. Eremenko Stary Oskol Russia Institute of Control Sciences of RAS N.a. V.A. Trapeznikov Adaptive and Robust Systems Laboratory N.a. Ya.Z. Tsypkin Moscow Russia

ISBN: (纸本)9798350309126

The problems of trolley position tracking and stabilization of the suspended load are solved simultaneously for an overhead crane. The model of the trolley-pendulum system is derived. To solve the problem under consideration, a nonlinear control law is designed using the second Lyapunov method, which guarantees asymptotic stability of the control error. The derived law is validated via numerical experiments. The obtained results corroborate the effectiveness of the proposed solution. © 2023 IEEE.

关键词： Lyapunov functions

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Linking intra- and extra-cellular metabolic domains via neural-network surrogates for dynamic metabolic control 10

Linking intra- and extra-cellular metabolic domains via neur...

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10th IFAC conference on Foundations of systems Biology in Engineering (FOSBE)

作者： Espinel-Rios, Sebastian Avalos, Jose L. Princeton Univ Dept Chem & Biol Engn Princeton NJ 08544 USA Princeton Univ Omenn Darling Bioengn Inst Princeton NJ 08544 USA Princeton Univ Andlinger Ctr Energy & Environm Princeton NJ 08544 USA Princeton Univ High Meadows Environm Inst Princeton NJ 08544 USA

We outline a modeling and optimization strategy for investigating dynamic metabolic engineering interventions. Our framework is particularly useful at the early stages of research and development, often constrained by limited knowledge and experimental data. Elucidating a priori optimal trajectories of manipulatable intracellular fluxes can guide the design of suitable control schemes, e.g., cyber(ge)netic or in-cell approaches, and the selection of appropriate actuators, e.g., at the transcriptional or post-translational levels. Model-based dynamic optimization is proposed to predict optimal trajectories of target manipulatable intracellular fluxes. A challenge emerges as existing models are often oversimplified, lacking insights into metabolism, or excessively complex, making them difficult to build and implement. Here, we use surrogates derived from steady-state solutions of constraint-based metabolic models to link manipulatable intracellular fluxes to the process exchange rates of structurally simple hybrid dynamic models. The latter can be conveniently used in optimal control problems of metabolism. As a proof of concept, we apply our method to a reduced metabolic network of Escherichia coli considering two different scenarios of dynamic metabolic engineering. Copyright (c) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： Hybrid modeling surrogate modeling flux balance analysis macro-kinetic modeling dynamic metabolic engineering

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