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16th APCA International Conference on Automatic control and Soft Computing, controlO 2024

作者： Nicu, Theodor-Gabriel Stoican, Florin Ioan, Daniel Prodan, Ionela Department of Automatic Control and Systems Engineering Romania National University of Science and Technology "Politehnica" Bucharest 313 Splaiul Independenţei Bucharest060042 Romania Univ. Grenoble Alpes Grenoble INP Institute of Engineering and Management LCIS Valence26000 France

ISBN: (纸本)9783031817236

This work pertains to the generation of navigation functions for obstacle avoidance and target tracking. One initially defines a so-called spherical world which can be further mapped into many other different topologies using a series of diffeomorphic transformations. This specific configuration further allows one to exploit the main advantages of the sum function approach with respect to the obstacle collision avoidance capabilities of an agent, sum function which is used in order to induce an effective navigation function judging not only from computational perspective, but also from the local minima point of view. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Topology

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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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Automatic Nonlinear MPC Approximation with Closed-loop Guarantees

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IEEE Transactions on Automatic control 2025年

作者： Tokmak, Abdullah Fiedler, Christian Zeilinger, Melanie N. Trimpe, Sebastian Kohler, Johannes Aalto University Department of Electrical Engineering and Automation Espoo02150 Finland RWTH Aachen University Institute for Data Science in Mechanical Engineering Aachen52068 Germany ETH Zurich Institute for Dynamic Systems and Control ZurichCH-8092 Switzerland

Safety guarantees are vital in many control applications, such as robotics. Model predictive control (MPC) provides a constructive framework for controlling safety-critical systems but is limited by its computational complexity. We address this problem by presenting a novel algorithm that automatically computes an explicit approximation to nonlinear MPC schemes while retaining closed-loop guarantees. Specifically, the problem can be reduced to a function approximation problem, which we then tackle by proposing Alkia-x, the Adaptive and Localized Kernel Interpolation Algorithm with eXtrapolated reproducing kernel Hilbert space norm. Alkia-x is a non-iterative algorithm that ensures well-conditioned computations, a fast-to-evaluate approximating function, and the guaranteed satisfaction of any desired bound on the approximation error. Hence, Alkia-x automatically computes an explicit function that approximates the MPC, yielding a controller suitable for safety-critical systems and high sampling rates. We apply Alkia-x to approximate two nonlinear MPC schemes, demonstrating reduced computational demand and applicability to realistic problems. © 1963-2012 IEEE.

关键词： Predictive control systems

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Distributed Least-Squares Optimization Solvers with Differential Privacy

arXiv

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arXiv 2024年

作者： Liu, Weijia Wang, Lei Guo, Fanghong Wu, Zhengguang Su, Hongye Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou310027 China Department of Automation Zhejiang University of Technology Hangzhou China

This paper studies the distributed least-squares optimization problem with differential privacy requirement of local cost functions, for which two differentially private distributed solvers are proposed. The first is established on the distributed gradient tracking algorithm, by appropriately perturbing the initial values and parameters that contain the privacy-sensitive data with Gaussian and truncated Laplacian noises, respectively. Rigorous proofs are established to show the achievable tradeoff between the (ǫ, δ)-differential privacy and the computation accuracy. The second solver is established on the combination of the distributed shuffling mechanism and the average consensus algorithm, which enables each agent to obtain a noisy version of parameters characterizing the global gradient. As a result, the least-squares optimization problem can be eventually solved by each agent locally in such a way that any given (ǫ, δ)-differential privacy requirement can be preserved while the solution may be computed with the accuracy independent of the network size, which makes the latter more suitable for large-scale distributed least-squares problems. Numerical simulations are presented to show the effectiveness of both solvers. © 2024, CC BY-NC-SA.

关键词： Parameter estimation

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Integrating Variable Reduction Strategy With Evolutionary Algorithms for Solving Nonlinear Equations systems

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 75-89页

作者： Aijuan Song Guohua Wu Witold Pedrycz Ling Wang School of Traffic and Transportation Engineering Central South UniversityChangsha 410075China Department of Electrical and Computer Engineering University of AlbertaEdmontonAB T6G 2V4Canada Department of Electrical and Computer Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddah 21589Saudi Arabia Systems Research Institute Polish Academy of SciencesWarsaw 01447Poland Department of Automation Tsinghua UniversityBeijing 100084China

Nonlinear equations systems(NESs)are widely used in real-world problems and they are difficult to solve due to their nonlinearity and multiple *** algorithms(EAs)are one of the methods for solving NESs,given their global search capabilities and ability to locate multiple roots of a NES simultaneously within one ***,the majority of research on using EAs to solve NESs focuses on transformation techniques and improving the performance of the used *** contrast,problem domain knowledge of NESs is investigated in this study,where we propose the incorporation of a variable reduction strategy(VRS)into EAs to solve *** VRS makes full use of the systems of expressing a NES and uses some variables(i.e.,core variable)to represent other variables(i.e.,reduced variables)through variable relationships that exist in the equation *** enables the reduction of partial variables and equations and shrinks the decision space,thereby reducing the complexity of the problem and improving the search efficiency of the *** test the effectiveness of VRS in dealing with NESs,this paper mainly integrates the VRS into two existing state-of-the-art EA methods(i.e.,MONES and DR-JADE)according to the integration framework of the VRS and EA,*** results show that,with the assistance of the VRS,the EA methods can produce better results than the original methods and other compared ***,extensive experiments regarding the influence of different reduction schemes and EAs substantiate that a better EA for solving a NES with more reduced variables tends to provide better performance.

关键词： Evolutionary algorithm(EA) nonlinear equations systems(ENSs) problem domain knowledge variable reduction strategy(VRS)

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Design and locomotion characteristic analysis of a novel tensegrity hopping robot

Design and locomotion characteristic analysis of a novel ten...

引用

2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

作者： Mo, Jixue Gao, Changqing Fang, Hao Yang, Qingkai Peng Cheng Laboratory Department of Strategic and Advanced Interdisciplinary Research Shenzhen518055 China Harbin Institute of Technology School of Mechanical Engineering and Automation Shenzhen518055 China Beijing Institute of Technology School of Automation Beijing100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

ISBN: (纸本)9798350325706

In consideration of the poor locomotion ability of most traditional tensegrity robot, a novel tensegrity hopping robot powered by push-pull electromagnets was proposed with better locomotivity. It is able to conduct stable consecutive progressing action and turning action through hopping. This paper covers the structural design, theoretical modeling of the robot's hopping process, as well as its self-righting analysis, simulation and experimental verification. The average moving speed and relative moving speed were measured to be 0.334m/s and 0.641 body length/s respectively, which obviously surpass the general moving ability of most traditional tensegrity robot. In addition, the robot was also validated to have good self-righting characteristic for stable consecutive hopping. Thus this robot can be potentially applied for search, rescue, detection, etc. in outdoor and unstructured environment. © 2023 IEEE.

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Action recognition through fusion of sEMG and skeletal data in feature level

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Journal of Ambient Intelligence and Humanized Computing 2022年第9期13卷 4125-4134页

作者： Wang, Xinming Ding, Weili Bian, Shuangshuang Liu, Honghai Department of Automation Institute of Electrical Engineering Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province Yanshan University 438 West of Hebei Avenue Haigang District Qinhuangdao066004 China School of Mechanical Engineering and Automation State Key Laboratory of Robotics and Systems Harbin Institute of Technology Shenzhen Nanshan District Shenzhen518055 China

Human action can be recognized through a unimodal way. However, the information obtained from a single mode is limited due to the fact that a single mode contains only one type of physical attribute. Therefore, it is motivational to improve the accuracy of actions through fusion of two different complementary modality, which are the surface electromyography (sEMG) and the skeletal data. In this paper, we propose a general framework of fusion of sEMG signals and skeletal data. Firstly, vector of locally aggregated descriptor (VLAD) was extracted from sEMG sequences and skeletal sequences, respectively. Secondly, features obtained from sEMG and skeletal data are mapped through different weighted kernels using multiple kernel learning. Finally, the classification results are obtained through the model of multiple kernel learning. A dataset of 18 types of human actions is collected via KinectV2 and Thalmic Myo armband to verify our ideas. The experimental results show that the accuracy of human action recognition are improved by combining skeletal data with sEMG signals. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Musculoskeletal system

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