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2023 International Conference on System Science and engineering, ICSSE 2023

作者： Lam, Le Hoang Truong, Nguyen Hoang Huy, Nguyen Minh Thanh, Truong Quoc Tran, Duc Thien Ho Chi Minh City University of Technology and Education Faculty of Electrical and Electronics Engineering Ho Chi Minh City70000 Viet Nam HCMC University of Technology Faculty of Mechanical Engineering Ho Chi Minh City70000 Viet Nam Ho Chi Minh City University of Technology and Education Automation Control Department Ho Chi Minh City70000 Viet Nam

ISBN: (纸本)9798350322941

This study investigates a force control method for free abrasive polishing to achieve a shiny metal surface finish. Despite the potential of this technique, this method is not widely used in metal surface polishing due to challenges in controlling the force during movement. To address the force control issue, we proposed an approach that uses the feedback force value indirectly calculated through the current value of the AC driver and applies it in a closed-loop control system. The proposed method is evaluated experimentally by polishing different metal pieces with varying particle sizes and movement speeds. The experimental results demonstrate that the proposed force control method effectively maintains a constant force during the polishing process, which leads to an improved surface finish. They also show that decreasing particle size and movement speed can improve the surface finish, while the contact force has a limited effect. These findings contribute to a better understanding of the relationship between force, movement speed, and surface finish quality in metal polishing. © 2023 IEEE.

关键词： Force control

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A Dynamic Safe Arbitrator for Human-Machine Shared control

A Dynamic Safe Arbitrator for Human-Machine Shared Control

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2022 Chinese automation Congress, CAC 2022

作者： Chen, Haocong Chen, Yutao Wang, Wu Lin, Dingci Huang, Jie Fuzhou University 5G+Industrial Internet Institute Fuzhou350108 China Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350108 China Fuzhou University College of Electrical Engineering and Automation Fuzhou350108 China

ISBN: (纸本)9781665465335

Shared control has become a popular subject of human-machine hybrid intelligence. This paper presents a dynamic safety arbitrator for shared control in an automated vehicle. The vehicle is controlled autonomously by a model predictive controller (MPC) tracking a given trajectory, while at the same time human input is provided via a joystick. Unlike traditional mixed-initiative control methods that blend weighted human and vehicle inputs, the proposed arbitrator first adopts control barrier function (CBF) to generate weights for human and vehicle inputs under safety critical situations, and then employs the null-space based control (NSBC) to merge the two inputs with priorities determined by the weights. As a result, the final input to the vehicle has a clear physical meaning that represents dynamic priorities of human and vehicle autonomous inputs, in which the higher priority input is fully adopted and the lower priority input is partially adopted without intervening the higher priority input. An immediate advantage of the proposed arbitrator is that there is no need to tune the weights between human and autonomous inputs. Simulation results show that the dynamic safe arbitrator is effective for shared control. © 2022 IEEE.

关键词： Safety engineering

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Distributed Optimization via Gradient Descent with Event-Triggered Zooming Over Quantized Communication

Distributed Optimization via Gradient Descent with Event-Tri...

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IEEE Conference on Decision and control

作者： Apostolos I. Rikos Wei Jiang Themistoklis Charalambous Karl H. Johansson Department of Electrical and Computer Engineering Division of Systems Engineering Boston University Boston MA US Department of Electrical and Computer Engineering School of Engineering University of Cyprus Aalto University Nicosia Cyprus Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Division of Decision and Control Systems KTH Royal Institute of Technologyy Stockholm Sweden

In this paper, we study unconstrained distributed optimization strongly convex problems, in which the exchange of information in the network is captured by a directed graph topology over digital channels that have limited capacity (and hence information should be quantized). Distributed methods in which nodes use quantized communication yield a solution at the proximity of the optimal solution, hence reaching an error floor that depends on the quantization level used; the finer the quantization the lower the error floor. However, it is not possible to determine in advance the optimal quantization level that ensures specific performance guarantees (such as achieving an error floor below a predefined threshold). Choosing a very small quantization level that would guarantee the desired performance, requires information packets of very large size, which is not desirable (could increase the probability of packet losses, increase delays, etc) and often not feasible due to the limited capacity of the channels available. In order to obtain a communication-efficient distributed solution and a sufficiently close proximity to the optimal solution, we propose a quantized distributed optimization algorithm that converges in a finite number of steps and is able to adjust the quantization level accordingly. The proposed solution uses a finite-time distributed optimization protocol to find a solution to the problem for a given quantization level in a finite number of steps and keeps refining the quantization level until the difference in the solution between two successive solutions with different quantization levels is below a certain pre-specified threshold. Therefore, the proposed algorithm progressively refines the quantization level, thus eventually achieving low error floor with a reduced communication burden. The performance gains of the proposed algorithm are demonstrated via illustrative examples.

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A Parkinson's Bradykinesia Recognition System Based on Deep Learning Method 12

A Parkinson's Bradykinesia Recognition System Based on Deep ...

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12th International Conference on CYBER Technology in automation, control, and Intelligent Systems, CYBER 2022

作者： Tong, Lina Liu, Daisong Zhang, Mingjia Peng, Liang Department of State Key Laboratory of Management and Control for Complex Systems Institute of Automation China Academy of Science Beijing China School of Mechanical Electronic and Information Engineering Chinese University of Mining and Technology-Beijing Beijing China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Parkinson's disease is a neurodegenerative disease common in middle-aged and elderly people, and bradykinesia is one of the most obvious symptoms. In this study, A deep learning-based Parkinson's bradykinesia recognition system is designed which has an inertial sensor-based data acquisition system. It can wirelessly collect bradykinesia kinematic information by wearing it on the wrist and ankle of Parkinson's patients. In addition, a method for identifying the symptom of Parkinson's bradykinesia based on Long Short Term Memory (LSTM) Network is proposed, with an accuracy of 98.6%. It provides a feasible method to identify Parkinson bradykinesia to assist the diagnosis and treatment. © 2022 IEEE.

关键词： Neurodegenerative diseases

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Platoon Keeping and Collision Avoidance Based on Distributed Model Predictive control under Arbitrary Communication Chain Malfunction

Platoon Keeping and Collision Avoidance Based on Distributed...

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2022 Chinese automation Congress, CAC 2022

作者： Chen, Nan Chen, Yutao Lin, Dingci Huang, Jie College of Electrical Engineering and Automation Fuzhou University Fuzhou350108 China Fuzhou University 5G+Industrial Internet Institute Fuzhou350108 China Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350108 China

ISBN: (纸本)9781665465335

In this paper, a platoon keeping and collision avoidance method based on distributed model predictive control(DMPC) is proposed to solve the problem of arbitrary communication chain malfunctions under a bidirectional-leader topology. Firstly, for the platoon under normal communication, a DMPC controller is designed by using the trajectory information of the leader and predecessor vehicle, which also satisfies the situation when communication chain between the follower (except follower 1) and the leader malfunction. Secondly, for other communication chain malfunction situation, we proposed the corresponding communication topology transformation scheme and controller transformation scheme, which makes the proposed control scheme can adapt to arbitrary communication chain malfunction situation. Finally, as for the control strategy proposed in this paper, some simulation experiments are carried out. © 2022 IEEE.

关键词： Collision avoidance

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Multi-objective optimization method of blast furnace operation performance indicators based on data and knowledge

Multi-objective optimization method of blast furnace operati...

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第35届中国控制与决策会议

作者： Duojin Yan Chunjie Yang Bo Yang Yu Chen Liyuan Kong Jian Chen College of Control Science and Engineering Zhejiang University Department of Automation Tsinghua University Jiangsu Binxin Iron and Steel Group Co.Ltd.

During blast furnace(BF) ironmaking,hot metal quality and energy consumption directly affect industrial economic *** engineers usually adjust the production state based on their experience,which makes control optimization uncertain.A data and knowledge-based optimization framework for BF operation performance indicators is proposed in this ***,design the Attention Long Short Term Memory(Attention-LSTM) neural network to predict the Silicon content and coke ratio,which is used as fitness value function of the multi-objective optimization *** initialize the population,knowledge based non-dominated sorting genetic algorithm(KB-NSGA) uses a knowledge base of historical optimal ***,an optimization solution set that meets the actual production requirements is obtained using the TOPSIS evaluation *** KB-NSGA successfully achieves the goal compared with other genetic *** effectiveness of the proposed method is verified by long-term running experiments.

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Towards Energy Efficient control for Commercial Heavy-Duty Mobile Cranes: Modeling Hydraulic Pressures using Machine Learning

arXiv

引用

arXiv 2023年

作者： Taheri, Abdolreza Pettersson, Robert Gustafsson, Pelle Pajarinen, Joni Ghabcheloo, Reza Control Systems R&D HIAB Hudiksvall Sweden Faculty of Engineering and Natural Sciences Tampere University Tampere Finland Department of Electrical Engineering and Automation Aalto University Espoo Finland

A sizable part of the fleet of heavy-duty machinery in the construction equipment industry uses the conventional valve-controlled load-sensing hydraulics. Rigorous climate actions towards reducing CO2 emissions has sparked the development of solutions to lower the energy consumption and increase the productivity of the machines. One promising solution to having a better balance between energy and performance is to build accurate models (digital twins) of the real systems using data together with recent advances in machine learning/model-based optimization to improve the control systems. With a particular focus on real-world machines with multiple flow-controlled actuators and shared variable-displacement pumps, this paper presents a generalized machine learning approach to modeling the working pressure of the actuators and the overall pump pressures. The procedures for deriving reaction forces and flow rates as important input variables to the surrogate models are described in detail. Using data from a real loader crane testbed, we demonstrate training and validation of individual models, and showcase the accuracy of pressure predictions in five different experiments under various utilizations and pressure levels. © 2023, CC BY.

关键词： Energy utilization

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LESS-Map: Lightweight and Evolving Semantic Map in Parking Lots for Long-term Self-Localization

arXiv

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arXiv 2023年

作者： Liu, Mingrui Tang, Xinyang Qian, Yeqiang Chen, Jiming Li, Liang College of Control Science and Engineering Zhejiang University Hangzhou310027 China Department of Automation Shanghai Jiao Tong University Shanghai200240 China

Precise and long-term stable localization is essential in parking lots for tasks like autonomous driving or autonomous valet parking, etc. Existing methods rely on a fixed and memory-inefficient map, which lacks robust data association approaches. And it is not suitable for precise localization or long-term map maintenance. In this paper, we propose a novel mapping, localization, and map update system based on ground semantic features, utilizing low-cost cameras. We present a precise and lightweight parameterization method to establish improved data association and achieve accurate localization at centimeter-level. Furthermore, we propose a novel map update approach by implementing high-quality data association for parameterized semantic features, allowing continuous map update and refinement during re-localization, while maintaining centimeter-level accuracy. We validate the performance of the proposed method in real-world experiments and compare it against state-of-the-art algorithms. The proposed method achieves an average accuracy improvement of 5cm during the registration process. The generated maps consume only a compact size of 450 KB/km and remain adaptable to evolving environments through continuous update. Copyright © 2023, The Authors. All rights reserved.

关键词： Semantics

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Attention-based Dynamic Latent Variable Modeling Method for Process Monitoring

Attention-based Dynamic Latent Variable Modeling Method for ...

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Asian control Conference

作者： Jingxiang Liu Weimin Zhu Guoqing Mu Jie Hou Junhui Chen School of Marine Electrical Engineering Dalian Maritime University Dalian China School of Information and Control Engineering Qingdao University of Technology Qingdao China College of Automation Chongqing University of Posts and Telecommunications Chongqing China Department of Chemical Engineering Chung-Yuan Christian University Taoyuan Taiwan

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

This study addresses the underexplored challenge of inherent dynamics in industrial processes through an innovative attention-based latent variable modeling method. Utilizing attention mechanisms, the method articulates time-variant dynamical relationships among samples. The framework extends attention-based dynamical inner principal component analysis to extract latent dynamical features, integrating them with static features obtained through static principal component analysis. This results in comprehensive monitoring statistics for online applications. Numerical simulations and real-world application in an industrial ethylene oxychlorination process demonstrate the proposed method's efficacy. Comparative analysis highlights its advantages and superior performance over existing methods. This innovative approach provides more accurate insights into complex industrial processes, promising advancements in data-driven modeling within the field.

关键词： Process monitoring Data-driven modeling Attention mechanisms Accuracy Feature extraction Numerical simulation Numerical models

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Dynamic Event-Triggered Quadratic Nonfragile Filtering for Non-Gaussian Systems:Tackling Multiplicative Noises and Missing Measurements

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1127-1138页

作者： Shaoying Wang Zidong Wang Hongli Dong Yun Chen Guoping Lu College of Science Shandong University of AeronauticsBinzhou 256603China College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590 Department of Computer Science Brunel University LondonUxbridge UB83PHUK Artificial Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum UniversityDaqing 163318China School of Automation Hangzhou Dianzi UniversityHangzhou 310018China School of Electrical Engineering Nantong UniversityNantong 226019China

This paper focuses on the quadratic nonfragile filtering problem for linear non-Gaussian systems under multiplicative noises,multiple missing measurements as well as the dynamic event-triggered transmission *** multiple missing measurements are characterized through random variables that obey some given probability distributions,and thresholds of the dynamic event-triggered scheme can be adjusted dynamically via an auxiliary *** attention is concentrated on designing a dynamic event-triggered quadratic nonfragile filter in the well-known minimum-variance *** this end,the original system is first augmented by stacking its state/measurement vectors together with second-order Kronecker powers,thus the original design issue is reformulated as that of the augmented ***,we analyze statistical properties of augmented noises as well as high-order moments of certain random *** the aid of two well-defined matrix difference equations,we not only obtain upper bounds on filtering error covariances,but also minimize those bounds via carefully designing gain ***,an example is presented to explain the effectiveness of this newly established quadratic filtering algorithm.

关键词： filtering quadratic bounds

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