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SICE Annual Conference

作者： Yoshihito Kinoshita Takayuki Ishizaki Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo JAPAN

ISBN: (数字)9784907764838

ISBN: (纸本)9798331544461

As a power system operation, a generation schedule indicating optimal on/off and power generation of generators is created so that the power needed by consumers can be generated and transmitted on transmission lines under some uncertainties. To create the economic schedule, we are required to solve a large-scale combinatorial optimization, which takes a long computation time to solve. Therefore, to reduce the computation time, the number of scenarios modeling the uncertainties is reduced based on dual variables which show the importance of the operational constraint violations in the linear relaxed optimization problem. To evaluate the performance of the proposed method, it is applied to the IEEE-118 bus power system model. The results show that the proposed method can reduce the computation time by up to 11% while maintaining the accuracy of the optimization solution.

关键词： Schedules Uncertainty Power transmission lines Computational modeling Stochastic processes Linear programming Generators Power systems Optimization Power generation

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A High-Precision Edge Detection Algorithm Based on Improved Sobel Operator-Assisted HED 14

A High-Precision Edge Detection Algorithm Based on Improved ...

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14th IEEE International Conference on Cyber Technology in automation, control, and Intelligent systems, CYBER 2024

作者： Yuan, Yeborui Chen, Wenyuan Tang, Jie Yang, Jia School of Electrical Engineering and Automation Tianjin University of Technology Tianjin300384 China Shenyang Institute of Automation Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang State Key Laboratory of Robotics 110016 China University of Chinese Academy of Sciences Beijing100049 China School of Electrical Engineering and Automation Tianjin University of Technology Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems Tianjin300384 China

ISBN: (纸本)9798331506056

In response to the problem of poor detection performance of the traditional Sobel operator in edge detection, a high-precision edge detection algorithm based on Sobel operator-assisted Holistically-nested Edge Detection (HED) network was proposed, which is named ISAHED here. The algorithm is designed as follows. Firstly, an improved Sobel operator based on the traditional Sobel operator was proposed through adding gradient direction. Then, the image output by the improved Sobel operator is taken as the ground-truth image and as the end-to-end comparison object in a HED-like network. Finally, the ISAHED algorithm outputs edge images with better quality through iterative learning of the HED-like neural network. The experimental results prove that the proposed ISAHED algorithm has better edge detection performance by visually observing the final edge images and further evaluating the values of FOM. This work provides an important reference for the further development of the edge detection technology. © 2024 IEEE.

关键词： Contrastive Learning

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Modified Deep Deterministic Policy Gradient Based Optimal Speed Tracking Strategy for PMSMs 13

Modified Deep Deterministic Policy Gradient Based Optimal Sp...

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13th IEEE Data Driven control and Learning systems Conference, DDCLS 2024

作者： Fan, Zhong-Xin Tang, Lintao Li, Shihua Liu, Rongjie School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Florida State University Department of Statistics TallahasseeFL32304 United States

ISBN: (纸本)9798350361674

Achieving optimal speed regulation for permanent magnet synchronous motors (PMSMs) remains a challenging task, particularly in selecting the most suitable controller to meet desired objectives. This paper considers the optimal speed tracking problem of PMSMs. We employ a reinforcement learning algorithm to obtain optimal controller with a linear form. The reinforcement learning approach incorporates a critic-actor network structure, which approximates the value function and optimal control, respectively. Specifically, a weight updating method for the critic network is introduced, where the update of the actor network is guided by the critic network. Through data collection and neural network training, dynamic acquisition of the optimal controller gain is achieved. In addition, a novel activation function is implemented in the network, leading to improved control performance concerning dataset size and reduced training time. At final, a real-world PMSM application is presented along with comparisons to demonstrate effectiveness. The desire idea of resulting optimal controllers is not only applicable to linear systems but also capable of approximating arbitrary nonlinear optimal controllers, thus offering practical engineering versatility. © 2024 IEEE.

关键词： Reinforcement learning

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Finite-Time Sideslip Differentiator-Based LOS Guidance for Robust Path Following of Snake Robots

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 239-253页

作者： Yang Xiu Dongfang Li Miaomiao Zhang Hongbin Deng Rob Law Yun Huang Edmond Q.Wu Xin Xu the School of Mechatronical Engineering Beijing Institute of TechnologyBeijing 100081China the School of Electrical Engineering and Automation Fuzhou UniversityFuzhou 350108 the Antai College of Economics&Management Shanghai Jiao Tong UniversityShanghai 200240China the Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China the Asia-Pacific Academy of Economics and Management University of MacaoMacao 999078China the Department of Decision Science Macao University of Science and TechnologyMacao 999078China the Department of Automation Shanghai Jiao Tong Universityand also with the Key Laboratory of System Control and Information ProcessingMinistry of Education of ChinaShanghai 200240China the College of Mechatronics and Automation National University of Defense TechnologyChangsha 410073China IEEE

This paper presents a finite-time sideslip differentiator-based line-of-sight(LOS)guidance method for robust path following of snake ***,finite-time stable sideslip differentiator and adaptive LOS guidance method are proposed to counteract sideslip drift caused by cross-track *** proposed differentiator can accurately observe the cross-track error and sideslip angle for snake robots to avoid errors caused by calculating sideslip angle *** our method,the designed piecewise auxiliary function guarantees the finite-time stability of position ***,for the case of external disturbances and state constraints,a Barrier Lyapunov functionbased backstepping adaptive path following controller is presented to improve the robot’s *** uniform ultimate boundedness of the closed-loop system is proved by analyzing ***,a gait frequency adjustment-based virtual velocity control input is derived to achieve the exponential convergence of the tangential *** last,the availability and superiority of this work are shown through simulation and experiment results.

关键词： Line-of-sight(LOS) path following sideslip snake robot

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Fault Estimation and Fault-Tolerant control for a Class of Continuous-Time PWA systems: A Region-Dependent Intermediate Variable Observer Approach 13

Fault Estimation and Fault-Tolerant Control for a Class of C...

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13th IEEE International Conference on CYBER Technology in automation, control, and Intelligent systems, CYBER 2023

作者： Xu, Nuo Zhu, Yanzheng Chen, Xinkai College of Mechanical Engineering and Automation Huaqiao University Fujian Xiamen361021 China College of Electrical Engineering and Automation Shandong University of Science and Technology Shandong Qingdao266590 China Shibaura Institute of Technology Department of Electronic and Information Systems Saitama337-8570 Japan

ISBN: (纸本)9798350315196

In this paper, the design issues of both the fault estimation (FE) and fault-tolerant control (FTC) are investigated for a class of piecewise-affine (PWA) systems against actuator fault. Firstly, a novel region-dependent intermediate variable observer is designed to estimate the system states and the actuator fault simultaneously. Secondly, based on the above estimated information, a class of output-feedback-based PWA FTC strategies is proposed. Furthermore, by using two region-dependent Lyapunov functions and the S-procedure with an ellipsoidal outer approximation estimation method, sufficient conditions are obtained such that the estimation error system is uniformly asymptotically bounded and the closed-loop system is asymptotically stable with a guaranteed H8 performance index, respectively. Finally, the effectiveness of proposed methods is demonstrated via an illustrative example. © 2023 IEEE.

关键词： Lyapunov functions

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ReactAIvate: A Deep Learning Approach to Predicting Reaction Mechanisms and Unmasking Reactivity Hotspots 27

ReactAIvate: A Deep Learning Approach to Predicting Reaction...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Hoque, Ajnabiul Das, Manajit Baranwal, Mayank Sunoj, Raghavan B. Department of Chemistry Indian Institute of Technology Bombay India Department of Systems & Control Engineering Indian Institute of Technology India Tata Consultancy Services Research Mumbai India Centre for Machine Intelligence and Data Science Indian Institute of Technology Bombay India

ISBN: (纸本)9781643685489

A chemical reaction mechanism (CRM) is a sequence of molecular-level events involving bond-breaking/forming processes, generating transient intermediates along the reaction pathway as reactants transform into products. Understanding such mechanisms is crucial for designing and discovering new reactions. One of the currently available methods to probe CRMs is quantum mechanical (QM) computations. The resource-intensive nature of QM methods and the scarcity of mechanism-based datasets motivated us to develop reliable ML models for predicting mechanisms. In this study, we created a comprehensive dataset with seven distinct classes, each representing uniquely characterized elementary steps. Subsequently, we developed an interpretable attention-based GNN that achieved near-unity and 96% accuracy, respectively for reaction step classification and the prediction of reactive atoms in each such step, capturing interactions between the broader reaction context and local active regions. The near-perfect classification enables accurate prediction of both individual events and the entire CRM, mitigating potential drawbacks of Seq2Seq approaches, where a wrongly predicted character leads to incoherent CRM identification. In addition to interpretability, our model adeptly identifies key atom(s) even from out-of-distribution classes. This generalizabilty allows for the inclusion of new reaction types in a modular fashion, thus will be of value to experts for understanding the reactivity of new molecules. © 2024 The Authors.

关键词： Reaction intermediates

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Internet of Things Based Smart Irrigation System Using ESP WROOM32

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Journal on Internet of Things 2023年第1期5卷 45-55页

作者： Krish R.Mehta K.Jayant Naidu Madhav Baheti Dev Parmar A.Sharmila Department of Control and Automation School of Electrical EngineeringVellore Institute of TechnologyVellore632014India

Farming has been the most prominent and fundamental activity for *** the population has been mul-tiplying exponentially,the demand for agricultural yield is growing *** high demand in production through traditional farming methodologies often falls short in terms of efficiency due to the limitations of manual *** the era of digitization,smart agricultural solutions have been emerging through the windows of Internet of Things and Artificial Intelligence to improve resource management,optimize the process of farming and enhance the yield of crops,hence,ensuring sustainable growth of the increasing *** implementing modern technologies in the field of farming we can enable telemetry through which farmers can remotely monitor and gather real time data on the desired *** also gives accurate and precise measurements when compared to traditional measurement *** research paper focuses on an IoT based approach for smart monitoring using ESP WROOM 32 microcontroller that helps farmers identify real-time parameters of temperature,moisture and humidity of their ***-time data on temperature,moisture,and humidity enables farmers to make informed decisions about irrigation and crop ***,the use of smart monitoring ensures accurate and precise measurements,surpassing the limitations of traditional techniques.

关键词： Smart monitoring IoT ESP WROOM 32 DHT11 soil moisture sensor smart agriculture

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A novel crack detection equipment for existing concrete structures and its validation testing 20th

A novel crack detection equipment for existing concrete stru...

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20th fib Symposium on ReConStruct: Resilient Concrete Structures, 2024

作者： Wang, Ruilin Zhang, Weiping Yu, Youling Jiang, Chao Liu, Jinyi Qiu, Junli Liu, Yang Department of Structural Engineering Tongji University Shanghai200092 China Tongji University Shanghai200092 China Department of Control Science and Engineering Tongji University Shanghai200092 China Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai200092 China

ISBN: (纸本)9782940643257

The application of computer vision technology in crack identification is becoming increasingly mature and has gradually become the main method of crack detection. However, digital cameras are still the image data collection equipment, and it is difficult to obtain the location information and true geometric dimensions of cracks. This paper proposes a new equipment with numerous sensors that can collect pictures and inertial unit data during the acquisition process, enabling fast and convenient data acquisition. By combining visual-inertial SLAM with crack identification technology, accurate and efficient crack measurement and location can be performed based on the acquired data. The effectiveness of the proposed method is demonstrated through field testing, and the equipment has high potential in detection and localization of surface damage or defect. © fédération internationale du béton (fib).

关键词： Digital cameras

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Platoon control of connected vehicles with heterogeneous model structuresconsidering external disturbances

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Green Energy and Intelligent Transportation 2022年第3期1卷 94-102页

作者： Yongfu Li Zongyu Qin Hao Zhu Srinivas Peeta Xinbo Gao Key Laboratory of Intelligent Air-Ground Cooperative Control for Universities in Chongqing College of AutomationChongqing University of Posts and TelecommunicationsChongqing400065China Schools of Civil and Environmental Engineering and Industrial and Systems Engineering Georgia Institute of TechnologyAtlantaGA30332United States of America

This article studies the distributed cooperative control problem with the heterogeneous model structures and external disturbances for the connected vehicle(CV)*** propose a hierarchical framework to separate information flow topology from local dynamics control,which aims to deal with the heterogeneous model structures of CV *** hierarchical framework splits the control scheme into two layers,which include an observer in the upper-level layer and an integral sliding mode(ISM)controller in the lower-level ***,the conditions for the asymptotic stability of the CV platoon are derived and the effectiveness of the ISM controller is demonstrated through the Lyapunov *** research shows that compared with the traditional methods,the hierarchical framework does not need to specify the topology structure as a commonly used ***,numerical simulation results are performed to test the effectiveness and superiority of the developed controller.

关键词： Connected vehicle Platoon control Heterogeneity Disturbances Lyapunov method

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Modeling of an external force estimator for an end-effector of a robot by neural networks

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Journal of the Chinese institute of Engineers, Transactions of the Chinese institute of Engineers,Series A 2023年第8期46卷 895-904页

作者： Junplod, Goragod Kornmaneesang, Woraphrut Chen, Shyh-Leh Wongsa, Sarawan Department of Control Systems and Instrumentation Engineering King Mongkut’s University of Technology Thonburi Bangkok Thailand International Bachelor Program in Engineering Yuan Ze University Taoyuan Taiwan Department of Mechanical Engineering National Chung Cheng University Chiayi Taiwan Advanced Institute of Manufacturing with High-Tech Innovations National Chung Cheng University Chiayi Taiwan

This paper proposes a method to estimate external forces at the tip of a robot end-effector by using a neural network model. In order to avoid the use of an expensive force sensor in the training purpose, the proposed method implements the indirect training method by including the inverse dynamic model of the robot manipulator to the training algorithm with available information from a default robot system. In this method, the robot dynamics equations are necessary for the training, therefore a disturbance observer is adopted to deal with the existing uncertainties and errors. The performance of the proposed estimation method is evaluated through experiments of a 5-DOF robotic experimental platform, comparing to another existing estimation method using recurrent neural network with a type-1 disturbance observer for the external force estimation. The estimation results show that the behavior of the estimated external forces strongly correlates with the applied external forces and the proposed method is superior to the other method. © 2023 The Chinese institute of Engineers.

关键词： Recurrent neural networks

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