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Two-Stage Robust Optimization Under Decision Dependent Uncertainty

IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1295-1306页

作者： Yunfan Zhang Feng Liu Yifan Su Yue Chen Zhaojian Wang João P.S.Catalão State Key Laboratory of Power System and Generation Equipment the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Mechanical and Automation Engineering the Chinese University of Hong KongHong Kong SARChina Ministry of Education Key Laboratory of System Control and Information Processing the Department of AutomationShanghai Jiao Tong Universityand also with Shanghai Engineering Research Center of Intelligent Control and ManagementShanghai 200240China Faculty of Engineering of the University of Porto and Institute for Systems and Computer Engineering Technology and Science(INESC TEC)Porto 4200-465Portugal IEEE

In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.

关键词： Benders decomposition decision-dependent uncertainty endogenous uncertainty robust optimization(RO)

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PID-fuzzy switching-based strategy to heading control for remote operated vehicle

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Neural Computing and Applications 2024年 1-17页

作者： Xie, Baolong He, Shuping Cao, Xiang Wang, Honghai Stojanovic, Vladimir Shi, Kaibo School of Electrical Engineering and Automation Anhui University Hefei230039 China School of Artificial Intelligence Anhui University Hefei230039 China School of Computing and Artificial Intelligence Chaohu University Chaohu238024 China Department of Automatic Control Robotics and Fluid Technique Faculty of Mechanical and Civil Engineering University of Kragujevac Kraljevo36000 Serbia School of Electronic Information and Electrical Engineering Chengdu University Chengdu610106 China

Accurate heading control is the premise for underwater vehicles to complete underwater operations. In order to improve the performance of heading control, this paper proposes a heading control strategy based on PID-fuzzy switching. First, the force analysis of the steering motion was carried out to derive the dynamics model of the steering motion. Then, the whole heading control process is divided into two phases, steering phase and holding phase. Fuzzy control is used in the steering phase, and PID control is used in the holding phase. By setting the automatic switching switch, the control system can switch freely between the two to meet the needs of system adjustment under different errors. Finally, the performance of the established heading control system is verified through motion control simulations and pool experiments, and the proposed control strategy is compared with other methods. The results show that the control strategy can effectively achieve ROV heading control with good steady-state accuracy, and the overall performance has been greatly improved. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Fuzzy control

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Computational Methods For Water Quality Index Calculation Using Real-Time Measurement System

Computational Methods For Water Quality Index Calculation Us...

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Mediterranean Conference on Embedded Computing (MECO)

作者： Radmila Koleva Emil Zaev Darko Babunski Damjan Stefanovski Gerhard Rath Department of Hydraulic Engineering and Automation Faculty of Mechanical Engineering Skopje North Macedonia Chair of Automation University of Leoben MUL Leoben Austria

ISBN: (数字)9798350387568

ISBN: (纸本)9798350387575

The main focus point of this research is the analysis of the computational methods used for Water Quality Index (WQI) calculation using a real-time measurement System. For the calculations, a prototype of a cheap IoT system for measuring surface water quality has been used. The monitoring system incorporates sensors for temperature, turbidity (NTU), and pH. These parameters are measured through probes submerged directly into the water sample. The probes are connected to an Arduino Uno microcontroller, and through Bluetooth wireless communication, the measured data is transferred to a mobile device and displayed on an application. Also, the measured data are saved on a personal computer for their further processing. The collected data from the IoT system is calculated and presented in real time. Using real-time monitoring we can get instant information for the possible water contamination.

关键词： Temperature measurement Temperature sensors Wireless communication Turbidity Real-time systems Pollution measurement Sensors

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Adaptive Prescribed Finite-Time Bipartite Consensus control for Nonaffine Nonlinear MASs Under Structurally Unbalanced Topology

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3532-3541页

作者： Wang, Xiaomei Song, Yongduan Zhao, Xudong Wang, Huanqing Wang, Ding Niu, Ben Chongqing University School of Automation Chongqing400044 China Shandong Normal University School of Information Science and Engineering Shandong Jinan250014 China Dalian University of Technology School of Control Science and Engineering Liaoning Dalian116023 China Bohai University College of Mathematical Sciences Liaoning Jinzhou121013 China Beijing University of Technology Faculty of Information Technology Beijing100124 China Sichuan University School of Electrical Engineering Chengdu610065 China

This article investigates an adaptive bipartite consensus tracking control algorithm for a class of heterogeneous nonaffine nonlinear multiagent systems (MASs) with prescribed finite-time tracking performance under an unbalanced communication topology. In the case of an unbalanced digraph, a novel locally optimal bipartition strategy is proposed to transform the unbalanced communication topology into a structurally balanced one, thereby enabling the implementation of bipartite consensus tracking control. To achieve the expected tracking performance, the design philosophy focuses on developing a prescribed finite-time performance function (PFTPF), capable of preassigning the convergence time and accuracy precisely beforehand. The explored adaptive control algorithm can ensure that the whole signals concerning the closed-loop MASs remain bounded while the bipartite consensus errors converge to a predetermined range around zero within the prescribed finite time. Ultimately, the simulation results on robotic systems prove the availability of the developed design solution. © 2013 IEEE.

关键词： Topology

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Substation Personnel Smoking Detection Based On GhostNetV2-YOLOv5 6

Substation Personnel Smoking Detection Based On GhostNetV2-Y...

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6th International Symposium on Autonomous Systems, ISAS 2023

作者： Peng, Jishen Wang, Chang Li, Yang Chen, Hongtian Liaoning Technical University Faculty of Electrical and Control Engineering Huludao China Shanghai University School of Mechatronic Engineering and Automation Shanghai China Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai China

ISBN: (纸本)9798350316155

In substations, violations such as smoking may lead to equipment damage and even threaten the safety of personnel. In this paper, a GhostNetV2-YOLOv5 based algorithm for detecting smoking by substation personnel is proposed. The algorithm uses GhostNetV2 as the backbone network to improve the accuracy of the model while achieving real-time detection of smoking behavior. The experimental results show that the method can improve the detection speed of the model without reducing the detection accuracy, and compared with the original YOLOv5 algorithm, the total mAP is improved by 2.58% and the prediction speed is improved by 1.61 times, which is superior to other smoking detection networks and has practical application value. © 2023 IEEE.

关键词： Personnel

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Power Loss Analysis of Energy Management System with Model Predictive control in Mae Hong Son Microgrid 3

Power Loss Analysis of Energy Management System with Model P...

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3rd IEEE International Conference on Power Electronics, Intelligent control and Energy Systems, ICPEICES 2024

作者： Prapanwattana, Nattakit Dechawatanapaisal, Donlapat Banjerdpongchai, David Rajan, Abhishek Center of Excellence in Intelligent Control Automation for Process Systems Chulalongkorn University Faculty of Engineering Dept. of Electrical Engineering 254 Phayathai Rd Bangkok Pathumwan10310 Thailand National Institute of Technology Sikkim Dept. of Electrical Engineering South Sikkim Ravangla737139 India

ISBN: (纸本)9798350387193

Energy management system (EMS) is an important tool for energy efficiency and reliability of the power system. The optimal power dispatch of energy resources can be obtained using the nonlinear model predictive control (NMPC). It is formulated as an optimization problem subject to linear and nonlinear constraints. Although the existing system works well under the current conditions, power loss has not been considered. Power loss in transmission lines occurs due to their resistance and a high amount of power flow to loads connecting to the system. The power loss leads to decreased efficiency in the electrical system and reduces the lifespan of equipment because of the high temperature from loss. This paper aims to analyze the power loss in the Mae Hong Son (MHS) microgrid. To achieve the research objectives, we employ the EMS of MHS with NMPC and calculate power loss in transmission lines for a period of 7 days. EMS considers three objective functions, namely, total operating cost, total carbon dioxide emission, and combined economic and emission dispatch and take into account of three seasons consisting of rainy, winter, and summer. © 2024 IEEE.

关键词： Predictive control systems

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Video-based Gait Analysis with IMU and Industrial Cameras: A Pilot Study

Video-based Gait Analysis with IMU and Industrial Cameras: A...

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2024 Medical Technologies Congress, TIPTEKNO 2024

作者： Turan, Fatma Maghsoudi, Sanaz İlikçi, Hakan Ayvaz, Bora Ergenç, Ali Fuat Bilgili, Fuat Boğazici University Biomedical Engineering Istanbul Turkey Istanbul University Istanbul Faculty of Medicine Department of Orthopedics and Traumatology Istanbul Turkey Istanbul Technical University Control and Automation Engineering Department Istanbul Turkey İstanbul University Istanbul Turkey

ISBN: (纸本)9798331529819

In this study, we investigated the validity of using a two-dimensional gait analysis system, which employed industrial cameras and a custom-developed Inertial Measurement Unit system, compared to the gold standard three-dimensional Vicon gait analysis system. Four subjects with a mean age of 26.76 (SD: 0.71) were included in the study, and gait data was collected from their 8 limbs. Correlation analyses examined the relationship between the data obtained from the two-dimensional gait analysis system and the three-dimensional Vicon system. The study's results showed a high correlation for the hip and knee joints between the two systems, but a lower correlation for the ankle joint. This pilot study demonstrated the potential of using industrial cameras and IMU systems for practical gait analysis. © 2024 IEEE.

关键词： Joints (anatomy)

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Comparison of Different Gaussian Process Models and Applications in Model Predictive control 23

Comparison of Different Gaussian Process Models and Applicat...

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23rd International Conference on control, automation and Systems, ICCAS 2023

作者： Diepers, Florian Polke, Dominik Ahle, Elmar Softker, Dirk University of Applied Sciences Niederrhein Faculty of Electrical Engineering and Computer Science Krefeld Germany University of Duisburg-Essen Chair of Dynamics and Control Duisburg Germany

ISBN: (纸本)9788993215274

Most advanced control methods require a sufficiently accurate model of the system to be controlled. These models are becoming increasingly difficult to generate due to the increasing complexity of the underlying systems. To address this problem, data-driven models can be used. These kind of models are trained based on data of the dynamic system. They can be used for controller design and also be applied directly to control the system. In this work, a stochastic model predictive controller (SMPC) with a Gaussian process model (GP) is utilized. The main advantage of GPs is the construction of a dynamic system model with the possibility of determining the uncertainty of its own prediction. In this contribution, three different utilizations of prediction uncertainty in SMPC are compared. Additionally, two different implementations of dynamic GPs, nonlinear autoregressive exogenous GPs (GP-NARX) and a state-space model based on GPs (GP-SSM), are considered. All six test cases are compared based on an evaluation criterion that describes the resulting control performance. A simulated inverted pendulum, a benchmark for nonlinear and unstable systems, is used as test system. In this work, the combinations of different dynamic GPs and the application of their uncertainty prediction in SMPC are evaluated and compared. © 2023 ICROS.

关键词： Stochastic models

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DMD-Based Model Predictive control for a Coupled PDE-ODE System

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IFAC-PapersOnLine 2023年第2期56卷 4258-4263页

作者： Dirk Wolfram Thomas Meurer Chair of Automation and Control Faculty of Engineering Kiel University 24143 Kiel Germany Digital Process Engineering Group Institute for Mechanical Process Engineering and Mechanics Karlsruhe Institute of Technology (KIT) 76187 Karlsruhe Germany

Models resulting from the application of the finite element method (FEM) are usually high dimensional, thus in general preventing the application of optimal control concepts under real-time conditions. In this work a system consisting of the heat equation defined on a 3-dimensional domain with local in-domain thermal actuators is considered, whose modeling results in a coupled PDE-ODE description. Based on simulation data, a data driven reduced order model is determined using the Dynamic Mode Decomposition with control (DMDc). Based on the DMDc model a model predictive control (MPC) approach with state estimator is developed to realize a desired temperture profile on the given domain. The concept is evaluated involving the high-dimensional finite element model as plant model.

关键词： Distributed parameter systems Reduced order model Data-driven control Model predictive control Heat conduction

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Neural Network Regression Analysis of Magnetic Sensor Data for Spatial Magnet Positioning

Neural Network Regression Analysis of Magnetic Sensor Data f...

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Electrical, Electronic and Computing engineering (IcETRAN), International Conference on

作者： Vladimir Sibinović Mirko Raković Department of Automatic Control Faculty of Electronic Engineering University of Niš Niš Serbia Chair of Mechatronics Robotics and Automation Faculty of Technical Science Novi Sad Serbia

ISBN: (数字)9798350386998

ISBN: (纸本)9798350387001

This paper deals with the magnet position estimation based on the measurements from multiple Hall sensors. Estimation of the position is obtained from trained artificial neural networks. Data are gathered using a custom sensor board that has eight three-axis Hall sensors on it, and correlation between magnetic field and position was determined to be able to estimate position in X and Y directions. First measurements were made to determine the optimal height of the magnet for later data gathering. The outcome of the research was evaluated by comparing the ground truth with the estimated values of the best-trained network to determine the error of estimation. Precise measurement of the position of the magnet is intended to be used for the development of a tactile sensor that estimates the contact force through the displacement of the magnet in the deformable layer.

关键词： Magnetic field measurement Systematics Magnetic sensors Layout Estimation Tactile sensors Artificial neural networks

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