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18th European Conference on Management Leadership and Governance, ECMLG 2022

作者： Szaller, Ádám Fries, Christian Nick, Gábor Kádár, Botond Fraunhofer Institute for Manufacturing Engineering and Automation IPA Stuttgart Germany University of Stuttgart Institute of Industrial Manufacturing and Management IFF Germany Institute for Computer Science and Control Budapest Hungary Department of Manufacturing Science and Engineering Budapest University of Technology and Economics Budapest Hungary EPIC InnoLabs Nonprofit Ltd. Budapest Hungary

ISBN: (纸本)9781914587573

Nowadays, manufacturing companies face more difficulties than ever. Unrest in global supply chains triggered by fluctuating customer demand, raw material shortages and crises (Covid pandemic, global warming, wars) complicate the utilization of production resources necessary for economic success. Also, the rapidly changing environment causes existing production plans to be adapted, which results in order changes, causing additional costs for manufacturers. One solution to cope with these problems is cooperation and sharing resources: requesting capacity from partners when having shortages and offering them temporarily in case of excess capacity. In this paper, a platform-based resource sharing mechanism is investigated from the economic perspective. In the mechanism, requests and offers are matched by a central platform applying a complex matching logic. The platform provides valid alternatives based on the incoming ordersthat the requesting company can choose from. Companies are rating each other's performance after each interaction based on delivery accuracy;choosing between resource offers is made based on the cumulated rating about the offeror and the price of the offer. Within this paper, the aim is to investigate the resource sharing mechanism from the economic point of view based on an approach to the responsiveness of a supply chain structure to turbulence, to support decision-makers trying to cope with unexpected changes. For this purpose, here the mechanism is briefly introduced, and basic concepts about turbulences in supply chains are also presented. Cost types related to resource sharing manufacturing companies are distinguished, and the model is validated with agent-based simulation. A simulation experiment is performed to investigate the use-case of outsourced jobs having different price levels. Based on the experiment, it can be concluded that there is a price level limit in such a resource sharing federation, under which it is worth it to collaborate

关键词： Turbulence

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Model Predictive control for Signal Temporal Logic Specifications with Time Interval Decomposition

Model Predictive Control for Signal Temporal Logic Specifica...

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IEEE Conference on Decision and control

作者： Xinyi Yu Chuwei Wang Dingran Yuan Shaoyuan Li Xiang Yin Thomas Lord Department of Computer Science University of Southern California Los Angeles CA USA Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China

In this paper, we investigate the problem of Model Predictive control (MPC) of dynamic systems for high-level specifications described by Signal Temporal Logic (STL) formulae. Recent works show that MPC has the great potential in handling logical tasks in reactive environments. However, existing approaches suffer from the heavy computational burden, especially for tasks with large horizons. In this work, we propose a computationally more efficient MPC framework for STL tasks based on time interval decomposition. Specifically, we still use the standard shrink horizon MPC framework with Mixed Integer Linear Programming (MILP) techniques for open-loop optimization problems. However, instead of applying MPC directly for the entire task horizon, we decompose the STL formula into several sub-tasks with disjoint time horizons, and shrinking horizon MPC is applied for each short-horizon sub-task iteratively. To guarantee the satisfaction of the entire STL formula and to ensure the recursive feasibility of the iterative process, we introduce new terminal constraints to connect each sub-task. We show how these terminal constraints can be computed by an effective inner-approximation approach. The computational efficiency of our approach is illustrated by a case study.

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Deep Learning for Improved Aircraft Identification in Shared Airspace

SSRN

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SSRN 2024年

作者： Ahmed, Aisha Sir Elkhatem Engin, Seref Naci Malik, Zainab Abdalgadir, Shahd Aeronautical Engineering Department Sudan University of Science and Technology Khartoum407 Sudan Computer Engineering Department Yildiz Technical University Istanbul34220 Turkey Department of Electrical and Electronics Engineering Sakarya University of Applied Science Sakarya54050 Turkey Control and Automation Engineering Department Yildiz Technical University Istanbul34220 Turkey

Ensuring accurate identification of approaching aircraft is a crucial task for Air Traffic control (ATC) systems. This is essential to prevent misidentification accidents, occurring especially in shared airspace. Misidentification incidents may occur due to "Mistaken Identity" and a system malfunction that results in the aircraft crew being unable to respond to a radar control sector call, as well as radio signal problems due to bad weather. While military Identification Friend or Foe (IFF), and Automatic dependent surveillance-broadcast (ADS-B) systems have traditionally served this purpose, their reliability diminishes in cases where stealthy aircraft, during extreme weather conditions and spacious oceanic regions, are involved. In addition, radio signal- based surveillance systems are reliance on aircraft transponders. Under certain circumstances, this may pose a serious problem for the ATC. This paper introduces a novel approach utilizing deep Convolutional Neural Networks (CNN) for the identification of a type of approaching aircraft as either military or civilian, specifically applied to remote-sensing satellite imagery. The objective is to robustly and accurately determine the type of aircraft whether hostile or friendly to enhance radio signal-based surveillance systems detectability. Experimental evaluation incorporates three distinct datasets: noise-free datasets, noisy datasets, and images affected by varying illumination conditions. The experimental results reveal a remarkably high identification accuracy, averaging 99.50%, across both noise-free and augmented datasets. The introduction of noisy datasets is accomplished through the application of a median filter. However, the results also point out an intrinsic challenge posed by illumination variations that affect CNN classification accuracy. © 2024, The Authors. All rights reserved.

关键词： Air traffic control

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Impact of Customer Order Change Dimensions on Order Management

Impact of Customer Order Change Dimensions on Order Manageme...

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2022 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2022

作者： Fries, Christian Szaller, Adam Bauernhansl, Thomas Schuh, Gunther Fraunhofer Institute for Manufacturing Engineering and Automation Ipa Stuttgart70569 Germany University of Stuttgart Institute of Industrial Manufacturing and Management Iff Stuttgart70569 Germany Institute for Computer Science and Control Budapest1111 Hungary Bme Department of Manufacturing Science and Engineering Budapest1111 Hungary of Rwth Aachen University Aachen Germany

ISBN: (数字)9781665486873

ISBN: (纸本)9781665486873

Today, manufacturing companies are surrounded by constantly changing external influences. These entail the risk of inefficiencies in the operational process, especially when existing plans have to be adapted. A common trigger of such modifications are customer order changes. They cause unplanned costs, which endanger the profitability of the company. However, the estimation of these additional costs is complex and therefore missing in today's operation. This paper therefore defines customer order change types and determines their effects based on the Aachener PPS-Model. The individual processing areas of a customer order are described and mathematically formulated. Agent-based simulation is used to evaluate the critical change dimensions. Simulation experiments showed that the additional costs generated due to customer order changes decrease if the average relative date and quantity change are reduced. If both change scopes are reduced equally, in the case of reducing quantity, the additional costs are a slightly higher than in the case of reducing date change. © 2022 IEEE.

关键词： Sales

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Consensus control of Leader-Following Multi-Agent Systems in Directed Topology With Heterogeneous Disturbances

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IEEE/CAA Journal of Automatica Sinica 2021年第2期8卷 423-431页

作者： Qinglai Wei Xin Wang Xiangnan Zhong Naiqi Wu the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049and also with Qingdao Academy of Intelligent IndustriesQingdao 266109China the Department of Computer and Electrical Engineering and Computer Science Florida Atlantic UniversityBoca Raton FL33431 USA the Institute of Systems Engineering and Collaborative Laboratory for Intelligent Science and SystemsMacao University of Science and TechnologyMacao 999078China

This paper investigates the consensus problem for linear multi-agent systems with the heterogeneous disturbances generated by the Brown *** main contribution is that a control scheme is designed to achieve the dynamic consensus for the multi-agent systems in directed topology interfered by stochastic *** traditional ways,the coupling weights depending on the communication structure are static.A new distributed controller is designed based on Riccati inequalities,while updating the coupling weights associated with the gain matrix by state errors between adjacent *** introducing time-varying coupling weights into this novel control law,the state errors between leader and followers asymptotically converge to the minimum value utilizing the local *** the Lyapunov directed method and It?formula,the stability of the closed-loop system with the proposed control law is *** simulation results conducted by the new and traditional schemes are presented to demonstrate the effectiveness and advantage of the developed control method.

关键词： Consensus control directed topology external disturbance multi-agent(MA)systems

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Efficient STL control Synthesis Under Asynchronous Temporal Robustness Constraints

Efficient STL Control Synthesis Under Asynchronous Temporal ...

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IEEE Conference on Decision and control

作者： Xinyi Yu Xiang Yin Lars Lindemann Thomas Lord Department of Computer Science University of Southern California Los Angeles CA USA Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China

In time-critical systems, such as air traffic control systems, it is crucial to design control policies that are robust to timing uncertainty. Recently, the notion of Asynchronous Temporal Robustness (ATR) was proposed to capture the robustness of a system trajectory against individual time shifts in its sub-trajectories. In a multi-robot system, this may correspond to individual robots being delayed or early. control synthesis under ATR constraints is challenging and has not yet been addressed. In this paper, we propose an efficient control synthesis method under ATR constraints which are defined with respect to simple safety or complex signal temporal logic specifications. Given an ATR bound, we compute a sequence of control inputs so that the specification is satisfied by the system as long as each sub-trajectory is shifted not more than the ATR bound. We avoid combinatorially exploring all shifted sub-trajectories by first identifying redundancy between them. We capture this insight by the notion of instant-shift pair sets, and then propose an optimization program that enforces the specification only over the instant-shift pair sets. We show soundness and completeness of our method and analyze its computational complexity. Finally, we present various illustrative case studies.

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无人飞行器在不确定扰动下的动态目标跟踪

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Engineering 2024年第4期35卷 74-85页

作者： Yanjie Chen Yangning Wu Limin Lan Hang Zhong Zhiqiang Miao Hui Zhang Yaonan Wang School of Mechanical Engineering and Automation Fuzhou UniversityFuzhou 350108China Department of Computer Science Aberystwyth UniversityAberystwyth SY233DBUK School of Robotics Hunan UniversityChangsha 410082China College of Electrical and Information Engineering Hunan UniversityChangsha 410082China National Engineering Research Center of Robot Visual Perception and Control Technology Hunan UniversityChangsha 410082China

This study proposes an image-based visual servoing(IBVS)method based on a velocity observer for an unmanned aerial vehicle(UAV)for tracking a dynamic target in Global Positioning System(GPS)-denied *** proposed method derives the simplified and decoupled image dynamics of underactuated UAVs using a constructed virtual camera and then considers the uncertainties caused by the unpredictable rotations and velocities of the dynamic target.A novel image depth model that extends the IBVS method to track a rotating target with arbitrary orientations is *** depth model ensures image feature accuracy and image trajectory smoothness in rotating target *** relative velocities of the UAV and the dynamic target are estimated using the proposed velocity *** to the velocity observer,translational velocity measurements are not required,and the control chatter caused by noise-containing measurements is *** integral-based filter is proposed to compensate for unpredictable environmental disturbances in order to improve the antidisturbance *** stability of the velocity observer and IBVS controller is analyzed using the Lyapunov *** simulations and multistage experiments are conducted to illustrate the tracking stability,anti-disturbance ability,and tracking robustness of the proposed method with a dynamic rotating target.

关键词： Unmanned aerial vehicle Visual servoing Velocity observer Target tracking

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Data-Driven Learning and control with Event-Triggered Measurements

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IEEE Transactions on Automatic control 2025年

作者： Feng, Shilun Shi, Dawei Chen, Tongwen Shi, Ling Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing100081 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Clear Water Bay Kowloon Hong Kong

Event-triggered control has attracted considerable attention for its effectiveness in resource-restricted applications. To make event-triggered control as an end-to-end solution, a key issue is how to effectively learn unknown system dynamics from event-triggered measurements and consequently, develop a learning-based event-triggered controller. Existing works learn system dynamics based on periodic time-triggered measurements, and it is yet to know how to learn a controller with performance guarantee based on event-triggered measurements. To address this issue, we consider the problem of learning an event-triggered state feedback controller for an unknown linear system based on event-triggered state measurements in this work. In particular, we first analyze the event-triggered measurements within a set-membership framework. We prove that the estimation error belongs to a bounded ellipsoid determined by the historical measurements and the event-triggering condition. Subsequently, we demonstrate that all admissible systems compatible with the collected data samples can be explicitly represented in the form of quadratic matrix inequalities using the state estimates. With the acquired set of admissible systems, a co-design problem for the data-driven controller and event-triggering condition is solved using the linear matrix inequality technique, with guaranteed closed-loop stability and L2-gain performance. Finally, numerical examples and comparisons are provided to illustrate the effectiveness of the proposed event-triggered learning and control approach. © 1963-2012 IEEE.

关键词： Networked control systems

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Evaluation of Deep Training and Adapting Algorithms in Medical with De-Noising EEG 3

Evaluation of Deep Training and Adapting Algorithms in Medic...

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3rd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Abdulwahid, Ali Hadi Karetla, Girija Rani Ganesh, K.V.B. Kumar, A Suresh Radha, K. Shivakumar, K. Southern Technical University Engineering Technical College Control and Automation Engineering Department Basra Iraq Western Sydney University School of Computer Data and Mathematical Sciences Australia Koneru Lakshmaiah Education Foundation KL Business School Guntur Andhra Pradesh India Graphic Era Deemed to Be University Department of CSE India St. Martin's Engineering College Dept. of IT Secunderabad Telangana India SR University School of Computer Science and Artificial Intelligence Warangal Telangana India

ISBN: (纸本)9798350399264

An electroencephalogram that was captured with electrodes placed can easily get contaminated with a variety of artifacts. Here is a comparative of various electroencephalogram (EEG) de-noising techniques. Three alternative techniques are used to eliminate five different kinds of noise, and also the outcomes are evaluated. These three methods are just the Least Mean Square (LMS) technique, the Connected Neural Network, and also the Recursive Least-square (RLS) adaptable algorithm (FCNN). Period charts of the actual EEG signal, the noise EEG signal, and thus the predicted EEG signal are used to display the results. RRMSE and signal-to-noise ratio were utilized to compare the effectiveness of the 3 de-noising strategies in this study. Investigating the model parameters in this case, we discover the FCNN forecasts a better outcome compared to the other two methods. © 2023 IEEE.

关键词： Electroencephalography

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Language-Conditioned Affordance-Pose Detection in 3D Point Clouds

arXiv

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arXiv 2023年

作者： Nguyen, Toan Vu, Minh Nhat Huang, Baoru Van Vo, Tuan Truong, Vy Le, Ngan Vo, Thieu Le, Bac Nguyen, Anh FPT Software AI Center Viet Nam Automation & Control Institute TU Wien Vienna Austria Imperial College London United Kingdom Department of Computer Science & Computer Engineering University of Arkansas United States Faculty of Mathematics and Statistics Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Computer Science University of Science Viet Nam Department of Computer Science University of Liverpool United Kingdom

Affordance detection and pose estimation are of great importance in many robotic applications. Their combination helps the robot gain an enhanced manipulation capability, in which the generated pose can facilitate the corresponding affordance task. Previous methods for affodance-pose joint learning are limited to a predefined set of affordances, thus limiting the adaptability of robots in real-world environments. In this paper, we propose a new method for language-conditioned affordance-pose joint learning in 3D point clouds. Given a 3D point cloud object, our method detects the affordance region and generates appropriate 6-DoF poses for any unconstrained affordance label. Our method consists of an open-vocabulary affordance detection branch and a language-guided diffusion model that generates 6-DoF poses based on the affordance text. We also introduce a new high-quality dataset for the task of language-driven affordance-pose joint learning. Intensive experimental results demonstrate that our proposed method works effectively on a wide range of open-vocabulary affordances and outperforms other baselines by a large margin. In addition, we illustrate the usefulness of our method in real-world robotic applications. Our code and dataset are publicly available at https://***. © 2023, CC BY-NC-SA.

关键词： Robotics

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