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第32届中国控制与决策会议

作者： ZHU Xiao-yan LI Song-hua CAO Jiao-zhao SUN Jie ZHANG Shi-bang Engineering Training Center Shenyang Jianzhu University School of Mechanical Engineering Shenyang Jianzhu University State Key Laboratory of Rolling and Automation Northeastern University Information & Control Engineering Faculty Shenyang Jianzhu University

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

In the continuous pickling line,the acid temperature setup accuracy was low,which not only caused excessive pickling defects,but also caused excessive consumption of hydrochloric acid and a decrease in pickling *** order to solve this problem,the acid temperature setup model based on case-based reasoning(CBR) technology was established by using a large amount of production data with good temperature setting *** the model was put into operation on a 1450 mm pickling and rolling line,the average pickling defect ratio decreased from 14.99904% to 11.7332% and the fluctuation range of the pickling defect ratio was effectively *** application showed that the setup accuracy of the acid temperature model was effectively *** the number of strip steel production increases,the model has the adaptive ability to change with the working conditions,which is suitable for industrial promotion.

关键词： Case-based reasoning acid temperature pickling and rolling line similarity function pickling defect

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Mathematical modeling of flow washing of preserved rawhides

Mathematical modeling of flow washing of preserved rawhides

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Circuits, Systems, Communications and Computers (CSCC), International Conference on

作者： Dagmar Janáčová Pavel Mokrejš Vladimír Vašek Rudolf Drga Dept. of Automation and Control Engineering Faculty of Applied Informatics Tomas Bata University in Zlí n Zlín Dept. of Polymer Engineering Faculty of Technology Tomas Bata University in Zlín Zlín Dept. of Security Engineering Faculty of Applied Informatics Tomas Bata University in Zlín Zlín

ISBN: (纸本)9781665481878

This paper presents a mathematical model of flow washing with the initial volume of the washing bath of preserved raw hides by salt. The main result of this work is the determination of the concentration field of the preservative in the raw material depending on the washing time and the size of the washing water flow, based on the correct laboratory-determined diffusion coefficient of the preservative using a tortuous factor. The paper points out the usefulness of applying theoretical tools of chemical engineering in areas such as the tanning industry.

关键词： Industries Computers Computational modeling Chemical engineering Mathematical models Raw materials Integrated circuit modeling

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A Parallel and Asynchronous Blob Shape Descriptor Implemented in CMOS Technology

A Parallel and Asynchronous Blob Shape Descriptor Implemente...

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International Conference on Microelectronics, MIEL

作者： P. Bogacki M. Długosz T. Talaśka R. Długosz Aptiv Services Poland Kraków Poland Institute of Telecommunications Faculty of Computer Science Electronics and Telecommunications AGH University of Science and Technology Kraków Poland Faculty of Control Robotics and Electrical Engineering Institute of Automation and Robotics Division of Signal Processing and Electronic Systems Poznan University of Technology Poznan Poland Faculty of Telecommunication Computer Science and Electrical Engineering Bydgoszcz University of Science and Technology Bydgoszcz Poland

The paper presents a family of novel light blob shape descriptors for use in selected active safety algorithms used in Advanced Driver Assistance Systems (ADAS). One of the motivations was to obtain a descriptor that would ensure low computational complexity. This makes it easy to implement both in software and hardware. One assumption is that the location of the center of a given light spot is approximately known. The principle of its operation is then to count white pixels in selected directions, starting from this central point. A key issue here is an efficient way of determining indexes of particular pixels belonging to the image patch, as well as the location of points representing places where the white area turns into black. In the case of a hardware implementation, this can be done using a parallel circuit operating in asynchronous mode, without the need for a control clock.

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A New Modeling Approach for Stability of Micro/Nano Bubbles

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IFAC-PapersOnLine 2021年第14期54卷 144-148页

作者： Mustafa Doğan Ulviya Bunyatova Onur Ferhanoğlu Istanbul Technical University Faculty of Electrical-Electronics Engineering Department of Control and Automation Engineering 34469 Istanbul Turkey Baskent University Faculty of Engineering Department of Biomedical Engineering Baglica Kampusu 06790 Ankara Turkey Istanbul Technical University Faculty of Electrical-Electronics Engineering Department of Electronics and Communications Engineering 34469 Istanbul Turkey

Microbubbles and nanobubbles have several characteristics that are comparable with millimeter- and centimeter-sized bubbles. These characteristics are their small size, which results in large surface area and high bioactivity, low rising velocity, decreased friction drag, high internal pressure, large gas dissolution capacity, negatively charged surface, and ability to be crushed and form free radicals. controlling and modeling fundamental properties such as nucleation and of the dynamics of these bubbles is key to successfully exploiting their potential in the growing number of applications such as biomedical diagnosis and therapy, antimicrobial in aquaculture, environment, engineering, stock raising and marine industry. Laser-generated bubble dimensions can be characterized with an optical setup employing a high power continuous wave green laser for bubble generation. In this work, non-resonant, self-excited due to structurally nonlinear properties of the hydrogel, bubble formation was modeled as functions of well-controlled parameters of the colloidal media that is multi-layered and anisotropic, engineered uniquely.

关键词： nano bubbles anisotropic colloidal laser treatment modeling pump-probe

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Towards One Shot & Pick All: 3d-Oas, an End-to-End Framework for Vision Guided Top-Down Parcel Bin-Picking Using 3d Overlapping-Aware Instance Segmentation and Gnn

SSRN

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SSRN 2022年

作者： Zhao, Yi Yang, Jiacheng Wang, Shaocong Li, Xiaohui Faculty of Electronics and control Engineering Chang’An University Yanta District ShaanXi Xi'An710054 China School of Automation Southeast University Xuanwu District JiangSu Nanjing210096 China

Robotic Grasping and sorting is acknowledged as the most fundamental and significant manipulation task in industry. An ultimate goal of a Vision guided Robotic grasping system is to precisely and efficiently pick maximum objects with minimum shots and processing time of vision system. So far, applicable end-to-end perception and autonomously picking of hierarchically stacked objects has not been fully discussed in previous works. Especially, in the scenario of top-down parcel bin-picking where robots are required to perceive and pick up parcels from random stack. In this work, we focus on this challenging task by putting forward a novel end-to-end parcel bin-picking model termed 3D-OAS. Our proposal combines a 3D overlapping-aware instance segmentation and directed graph to describe the hierarchical structure of stacked objects from a top-down angle and a graph-neural-network is introduced to solve the optimal sorting orders. The experiment was conducted via a set of Vision guided Delta-Parallel robotic grasping system with a topdown RGB-D camera. Experimental Results proved the feasibility of our proposal, it could hierarchically segment stacked objects and solve sorting sequence with minimum one shot. © 2022, The Authors. All rights reserved.

关键词： Directed graphs

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A Nested Graph Reinforcement Learning-based Decision-making Strategy for Eco-platooning

arXiv

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arXiv 2024年

作者： Gao, Xin Li, Xueyuan Liu, Hao Li, Ao Ma, Zhaoyang Li, Zirui The School of Mechanical Engineering Beijing Institute of Technology Beijing China The School of Computer and Information Technology Beijing Jiaotong University Beijing China The Center for AI Safety and Governance Institute for AI Peking University Beijing100871 China The Chair of Traffic Process Automation "Friedrich-List" Faculty of Transport and Traffic Sciences TU Dresden Germany

Platooning technology is renowned for its precise vehicle control, traffic flow optimization, and energy efficiency enhancement. However, in large-scale mixed platoons, vehicle heterogeneity and unpredictable traffic conditions lead to virtual bottlenecks. These bottlenecks result in reduced traffic throughput and increased energy consumption within the platoon. To address these challenges, we introduce a decision-making strategy based on nested graph reinforcement learning. This strategy improves collaborative decision-making, ensuring energy efficiency and alleviating congestion. We propose a theory of nested traffic graph representation that maps dynamic interactions between vehicles and platoons in non-Euclidean spaces. By incorporating spatio-temporal weighted graph into a multi-head attention mechanism, we further enhance the model’s capacity to process both local and global data. Additionally, we have developed a nested graph reinforcement learning framework to enhance the self-iterative learning capabilities of platooning. Using the I-24 dataset, we designed and conducted comparative algorithm experiments, generalizability testing, and permeability ablation experiments, thereby validating the proposed strategy’s effectiveness. Compared to the baseline, our strategy increases throughput by 10% and decreases energy use by 9%. Specifically, increasing the penetration rate of CAVs significantly enhances traffic throughput, though it also increases energy consumption. Copyright © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

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Hardware-in-the-Loop Simulation of Vehicle-Manipulator Systems for Physical Interaction Tasks

Hardware-in-the-Loop Simulation of Vehicle-Manipulator Syste...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Hemjyoti Das Bjørn Kåre Sæbø Kristin Y. Pettersen Christian Ott Faculty of Electrical Engineering and Information Technology Automation and Control Institute (ACIN) Technical University of Vienna TU Wien Vienna Austria Department of Engineering Cybernetics Centre for Autonomous Marine Operations and Systems (NTNU AMOS) NTNU Norwegian University of Science and Technology Trondheim Norway German Aerospace Center Institute of Robotics and Mechatronics Wessling Germany

Hardware-in-the-loop simulation (HILS) allows a more realistic evaluation of control approaches than what is possible with pure software simulations, but without the actual complexity of the complete system. This is important for some complex systems such as orbital robots, where testing of the system is typically not possible after its launch, and an on-ground replica is used to validate the performance of such a system. In this article, an impedance-matching approach is presented to match the end-effector dynamics of a fixed-base robot manipulator with that of a target vehicle-manipulator system (VMS), while taking into account the redundant nullspace dynamics in a connected real-time simulation framework. This approach ensures that the forces and torques exerted by the system on the environment matches with that of the simulated system. The contact wrenches used in our approach are not obtained from numerical simulations, but rather from real physical interaction, which is one of the main advantages of our approach. The effectiveness of our method is validated by demonstrating various physical interaction tasks with the environment, using a suspended aerial manipulator as the target system.

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Lexicographic Multi-objective Order Picking Optimization for Robotic Mobile Fulfillment Systems

Lexicographic Multi-objective Order Picking Optimization for...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Hanying Wang Ziyan Zhao Jiaqi Liang Xingyang Li Shixin Liu College of Information Science and Engineering Northeastern University Shenyang China Foshan Graduate School of Innovation Northeastern University Foshan China Département de mathématiques et génie industriel Polytechnique Montréal Montréal Qc Canada Faculty of Robot Science and Engineering Northeastern University Shenyang China State Key Laboratory of Synthetical Automation for Process Industries and the College of Information Science and Engineering Northeastern University Shenyang China School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao Hebei China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

In light of advancements in artificial intelligence, the Internet of Things, and mechatronics, robots are increasingly integrated into e-commerce warehouses to enable smart order picking solutions and foster intelligent automation. A robot-assisted order picking process revolutionizes the traditional labor-intensive person-to-goods order picking technology, leading to a goods-to-person (G2P) smart warehouse. Within it, robots transport pods to predefined picking stations, where human pickers retrieve the requested goods from these pods to fulfill customer orders. The allocation of pods to robots and the scheduling of picking operations are key optimization issues in G2P order picking systems. Although they play a key role in improving operational efficiency, existing research has paid limited attention to their joint optimization. This study considers a lexicographic multi-objective optimization problem to shorten the order picking cycles under the premise of optimizing the picking efficiency evaluated by makespan. We build a mixed integer program for the newly proposed problem and develop a matheuristic algorithm by integrating a commodity-order model into a metaheuristic algorithm to solve it. Experimental results show that the proposed method can significantly shorten the total order picking cycles while keeping the minimum makespan. It outperforms a recent state-of-the-art algorithm. This work emphasizes the importance of joint optimization within G2P smart warehouses and reveals the high potential of the proposed method to be used in practice.

关键词： Intelligent automation Adaptation models Mechatronics Metaheuristics Search problems Scheduling Resource management Internet of Things Electronic commerce Robots

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Designing of A Plastic Garbage Robot With Vision-Based Deep Learning Applications

Designing of A Plastic Garbage Robot With Vision-Based Deep ...

引用

International Conference on System Science and engineering (ICSSE)

作者： Le Tien Thanh Le Hoang Lam Thanh Nha Nguyen Duc Thien Tran Automation Control Department Ho Chi Minh City University of Technology and Education Ho Chi Minh City Vietnam Faculty of Electrical and Electronics Engineering Ho Chi Minh City University of Technology and Education Ho Chi Minh City Vietnam

To address the issue of plastic waste, a robot using deep learning technology for visual recognition to classify plastic waste has been developed. This system includes a 3DOF robot arm, a conveyor, a camera, an electrical cabinet, and a computer. The object detection component of the system is designed using transfer learning with a pre-trained YOLOv5 model to ensure the system operates in real time. Selecting the best model by evaluating and comparing the results of models trained using labeling by bounding box and polygon methods. Then, the real-world coordinates for the origin of the robot arm are determined by utilizing matrices obtained from MATLAB through chessboard images. The computer processes the data and transmits commands to the robot arm system and conveyor, which is controlled by a PLC and 3 different Servo Drivers, for object sorting on the conveyor. The best-performing model has a Precision of 92.1% and a Recall of 87.3%, and the success rate of picking up an object is 91.5%. While the experimental results indicate complete stability in inter-device connectivity, implementing it would necessitate hardware improvements to leverage its potential.

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A K-Means Clustering-Based Optimization of IT2FL for Improved Regenerative Braking Performance

A K-Means Clustering-Based Optimization of IT2FL for Improve...

引用

Smart Mechatronics (ICSMech), IEEE International Conference on

作者： Muhammad Rizalul Wahid Endra Joelianto Bentang Arief Budiman Manida Tongroon Mulia Pratama Mahmudah Salwa Gianti Muhammad Fauzan Hernadi Mechatronics and Artificial Intelligence Universitas Pendidikan Indonesia Bandung Indonesia Instrumentation Control and Automation Research Group Institut Teknologi Bandung Bandung Indonesia Faculty of Mechanical and Aerospace Engineering Institut Teknologi Bandung Bandung Indonesia Department of Mechanical Engineering ATAE Research Unit Kasetsart University Sriracha Thailand Pusat Riset Mekatronika Cerdas Organisasi Riset Elektronika dan Informatika-BRIN Bandung Indonesia

ISBN: (数字)9798350368918

ISBN: (纸本)9798350368925

Optimizing regenerative braking systems in electric vehicles presents a complex challenge requiring precise and adaptable control. This research proposes employing K-Means Clustering to the Interval Type-2 Fuzzy Logic (IT2FL) membership functions, thereby improving overall regenerative braking efficiency and enhancing driving range. This research demonstrates that implementing a K-Means in the IT2FL control system in electric vehicles effectively recovers 35.84% of energy. By incorporating a K-means-based approach, the IT2FL controller further enhances vehicle range by 43 kilometers, achieving a total range of 108 kilometers. In comparison, an IT2FL system without K-means recovered only 26.67% of energy and achieved a total range of 93 kilometers. Notably, the IT2FL controller with K-means enabled the electric vehicle to attain an energy efficiency of 22 kilometers per kilowatt-hour. These findings underscore the significant improvement in maximum range offered by the IT2FL controller with K-means compared to alternative methods.

关键词： Fuzzy logic Energy consumption Electric potential Mechatronics Electric vehicles control systems Energy efficiency Optimization

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