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Distributed Event-Triggered Bandit Convex Optimization With Time-Varying Constraints

IEEE Transactions on Control of Network systems 2025年

作者： Zhang, Kunpeng Yi, Xinlei Wen, Guanghui Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China Ministry of Education Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Shanghai201210 China Southeast University School of Automation Nanjing210096 China University of Groningen Engineering and Technology Institute Groningen Faculty of Science and Engineering GroningenAG 9747 Netherlands KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm10044 Sweden KTH Royal Institute of Technology Digital Futures Stockholm10044 Sweden

This paper considers the distributed bandit convex optimization problem with time-varying inequality constraints over a network of agents, where the goal is to minimize network regret and cumulative constraint violation. Existing distributed online algorithms solving this problem require that each agent broadcasts its decision to its neighbors at each iteration. However, communication resources are often limited. To better utilize communication resources, we propose a distributed event-triggered online primal-dual algorithm with two-point bandit feedback. Under several classes of appropriately chosen decreasing parameter sequences and non-increasing event-triggered threshold sequences, we establish dynamic network regret and network cumulative constraint violation bounds. These bounds are comparable to the results achieved by distributed event-triggered online algorithms with full-information feedback. Finally, a numerical example is provided to verify the theoretical results. © 2014 IEEE.

关键词： Optimization algorithms

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Multi-Objective Optimization of Cloud Manufacturing Service Combination Based on Manufacturing and Logistics Coordinate

Multi-Objective Optimization of Cloud Manufacturing Service ...

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Chinese Control and Decision Conference, CCDC

作者： Sining Han Bingfeng Ge Wanying Wei Xiaonong Lu Zeqiang Hou Yuming Huang College of Systems Engineering National University of Defense Technology National University of Defense Technology Changsha China Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education University of Science and Technology of China Hefei China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

With the continuous emergence of new technologies, the manufacturing industry is facing unprecedented challenges. Manufacturing services typically involve various types of production equipment, diverse suppliers, and varied customer demands. Optimization in this context often encompasses multi pie objectives, necessitating timely adjustments in service comb ¡nations to meet customer needs. Traditional manufacturing models evidently fall short in resource allocation within manufacturing supply chains. Cloud manufacturing, proposed as a novel manufacturing model, aims to optimize resource allocation through the combination and configuration of resources, there by enhancing the efficiency of manufacturing supply chains. Logistics, as a crucial component within manufacturing supply chains, underscores the significance of coordinating the optimizad on of manufacturing and logistics services. This research focus es on the multi-objective optimization problem of cloud manufacturing service combinations. Building upon the execution process of manufacturing and logistics services for complex product manufacturing tasks, a novel mathematical model for the optimization of manufacturing resources and logistics resources i s constructed. The model utilizes the NSGA-H algorithm to coordinate the optimization processes of manufacturing and legistics resources. Finally, a case study demonstrates the effectiveness of the proposed model.

关键词： Costs Supply chains Production equipment Pareto optimization Mathematical models Manufacturing Resource management

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Dynamic Task Space Control Enables Soft Manipulators to Perform Real-World Tasks

arXiv

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arXiv 2022年

作者： Fischer, Oliver Toshimitsu, Yasunori Kazemipour, Amirhossein Katzschmann, Robert K. Department of Mechanical and Process Engineering Soft Robotics Laboratory Institute of Robotics and Intelligent Systems ETH Zurich Zurich8092 Switzerland

Dynamic motions are a key feature of robotic arms, enabling them to perform tasks quickly and efficiently. A majority of real-world soft robots rely on a quasistatic control approach, without taking dynamic characteristics into consideration. As a result, robots with this restriction move slowly and are not able to adequately deal with forces, such as handling unexpected perturbations or manipulating objects. A dynamic approach to control and modeling would allow soft robots to move faster and handle external forces more efficiently. In previous studies, different aspects of modeling, dynamic control, and physical implementation have been examined separately, while their combination has yet to be thoroughly investigated. Herein, the accuracy of the dynamic model of the multisegment continuum robot is improved by adding new elements that include variable stiffness and actuation behavior. Then, this improved model is integrated with state-of-the-art system identification and dynamic task space control and experiments are performed to validate this combination on a real-world manipulator. As a means of encouraging future research on dynamic control for soft robotic manipulators, the source code is made available for modeling, control, and system identification, along with the recipes for fabricating the manipulator. © 2022, CC BY.

关键词： Religious buildings

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A Fast Generation Algorithm of Communication Topology for Three-dimensional Optimally Persistent Formation 33

A Fast Generation Algorithm of Communication Topology for Th...

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第33届中国控制与决策会议

作者： Guoqiang Wang Qianwei Lv Xiaoduo Li Xin Cao He Luo School of Management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Engineering Research Center for Intelligent Decision-making & Information Systems Technologies Ministry of Education Key Laboratory of Urban ITS Technology Optimization and Integration Ministry of Public Security of China

ISBN: (纸本)9781665431293

To solve the communication topology generation problem of three-dimensional optimally persistent formation with leader constraint,a fast generation algorithm based on minimum cost arborescence,arc addition and path reverse operation is *** with the existing algorithms,this algorithm has a shorter calculation ***,the simulation results further verify the correctness and effectiveness of the algorithm.

关键词： Communication topology Leader constraint Three-dimensional optimal persistent formation Minimum cost arborescence Arc addition Path reverse operation

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Distributed Constrained Online Nonconvex Optimization with Compressed Communication

arXiv

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arXiv 2025年

作者： Zhang, Kunpeng Xu, Lei Yi, Xinlei Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Mechanical Engineering University of Victoria VictoriaBCV8W 2Y2 Canada Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai201210 China Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper considers distributed online nonconvex optimization with time-varying inequality constraints over a network of agents. For a time-varying graph, we propose a distributed online primal–dual algorithm with compressed communication to efficiently utilize communication resources. We show that the proposed algorithm establishes an O(T max{1−θ1,θ1}) network regret bound and an O(T 1−θ1/2) network cumulative constraint violation bound, where T is the number of iterations and θ1 ∈ (0, 1) is a user-defined trade-off parameter. When Slater’s condition holds (i.e, there is a point that strictly satisfies the inequality constraints at all iterations), the network cumulative constraint violation bound is reduced to O(T 1−θ1). These bounds are comparable to the state-of-the-art results established by existing distributed online algorithms with perfect communication for distributed online convex optimization with (time-varying) inequality constraints. Finally, a simulation example is presented to validate the theoretical results. Copyright © 2025, The Authors. All rights reserved.

关键词： Convex optimization

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Improving Accuracy of Optical Sorters Using Closed-Loop Control of Material Recirculation

Improving Accuracy of Optical Sorters Using Closed-Loop Cont...

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American Control Conference (ACC)

作者： Jonathan Vieth Marcel Reith-Braun Albert Bauer Florian Pfaff Georg Maier Robin Gruna Thomas Längle Harald Kruggel-Emden Uwe D. Hanebeck Intelligent Sensor-Actuator-Systems Laboratory Karlsruhe Institute of Technology Karlsruhe Germany Intelligent Sensor-Actuator-Systems Laboratory (ISAS) Karlsruhe Institute of Technology Karlsruhe Germany Chair of Mechanical Process Engineering and Solids Processing (MVTA) Technical University of Berlin Berlin Germany Fraunhofer Institute of Optronics System Technologies and Image Exploitation (IOSB) Karlsruhe

Optical sorting is a key technology for the circular economy and is widely applied in the food, mineral, and recycling industries. Despite its widespread use, one typically resorts to expensive means of adjusting the accuracy, e.g., by reducing the mass flow or changing mechanical or software parameters, which typically requires manual tuning in a lengthy, iterative process. To circumvent these drawbacks, we propose a new layout for optical sorters along with a controller that allows re-feeding of controlled fractions of the sorted mass flows. To this end, we build a dynamic model of the sorter, analyze its static behavior, and show how material recirculation affects the sorting accuracy. Furthermore, we build a model predictive controller (MPC) employing the model and evaluate the closed-loop sorting system using a coupled discrete element–computational fluid dynamics (DEM–CFD) simulation, demonstrating improved accuracy.

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Operational strategies for a photovoltaic-thermal system integrated with an electric air-to-water heat pump

Operational strategies for a photovoltaic-thermal system int...

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International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED)

作者： Giuseppe Russo Andreas V. Olympios Chandan Pandey Annamaria Buonomano Christos N. Markides Department of Chemical Engineering Clean Energy Processes (CEP) Laboratory and Sargent Centre for Process Systems Engineering Imperial College London UK Department of Industrial Engineering University of Naples Federico II Naples Italy Department of Electrical and Computer Engineering PV Technology Laboratory University of Cyprus Nicosia Cyprus PHAETHON Centre of Excellence for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus

ISBN: (数字)9798350375923

ISBN: (纸本)9798350375930

In this study, operational strategies are investigated for an air-based photovoltaic-thermal (PV-T) system integrated with a domestic air-to-water heat pump. The PV-T system is used to simultaneously generate electricity and heat ambient air, which serves as the heat source for the heat pump. By utilising a variable-speed fan to regulate airflow, the PV-T system outlet temperature is adjusted, and the focus is on how different outlet temperatures impact the PVT system electrical and thermal efficiency, heat pump performance, and overall electricity requirements for heating. The performance of the integrated system is assessed for a case study of a household application in north Italy. The optimal PV-T outlet temperature is found to be between 30 – 35 °C, resulting in only 5% less electricity production than an equivalent PV system with equal nominal electricity capacity, while reducing overall electricity required for heating by over 15% compared to PV-integrated heat pumps.

关键词： Photovoltaic systems Fans Temperature Heat pumps Electricity Buildings Water heating Production Temperature control Resistance heating

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One-Point Sampling for Distributed Bandit Convex Optimization with Time-Varying Constraints

arXiv

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arXiv 2025年

作者： Zhang, Kunpeng Xu, Lei Yi, Xinlei Wen, Guanghui Xie, Lihua Chai, Tianyou Yang, Tao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Mechanical Engineering University of Victoria VictoriaBCV8W 2Y2 Canada Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai201210 China Department of Mathematics Southeast University Nanjing210096 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore

This paper considers the distributed bandit convex optimization problem with time-varying constraints. In this problem, the global loss function is the average of all the local convex loss functions, which are unknown beforehand. Each agent iteratively makes its own decision subject to time-varying inequality constraints which can be violated but are fulfilled in the long run. For a uniformly jointly strongly connected time-varying directed graph, a distributed bandit online primal–dual projection algorithm with one-point sampling is proposed. We show that sublinear dynamic network regret and network cumulative constraint violation are achieved if the path–length of the benchmark also increases in a sublinear manner. In addition, an O(T3/4+g) static network regret bound and an O(T1−g/2) network cumulative constraint violation bound are established, where T is the total number of iterations and g ∈ (0, 1/4) is a trade-off parameter. Moreover, a reduced static network regret bound O(T2/3+4g/3) is established for strongly convex local loss functions. Finally, a numerical example is presented to validate the theoretical results. Copyright © 2025, The Authors. All rights reserved.

关键词： Convex optimization

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Robust Event-Triggered Control of Nonlinear systems Under a Global Sector-Bound Condition

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Guidance, Navigation and Control 2022年第2期2卷 59-79页

作者： Pengpeng Zhang Tengfei Liu Zhong-Ping Jiang Department of Control Science&Engineering Frontiers Science Center for Intelligent Autonomous SystemsTongji UniversityShanghai 201804P.R.China State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819P.R.China Department of Electrical and Computer Engineering New York University370 Jay StreetBrooklynNY 11201USA

This paper studies an event-tniggered control problem for nonlinear systems subject to both external disturbancoes and dy namic *** is assumed that the system satisfies a global sector bound *** avold infnitely fast samplng,a novel eventriggred sampling mechanism is propoeed,which use8 not only the measuned system state but also an estimation of the inluence of the *** the propoeed design,the intersampling intervals an be lower bounded by a poeitive constant,and it is independent of botb external disturbances and dynamie ***,the doeedl loop event-tniggered system i proved to be input-torstate stable with repect to the extemal *** smalgain techmigues are;used for the stability analysis of the dloeeil-bop system.

关键词： Event-triggered control external disturbance dynamic uncertainty input-to-state stability

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GridSort: Image-based Optical Bulk Material Sorting Using Convolutional LSTMs

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IFAC-PapersOnLine 2023年第2期56卷 4620-4626页

作者： Marcel Reith-Braun Albert Bauer Maximilian Staab Florian Pfaff Georg Maier Robin Gruna Thomas Längle Jürgen Beyerer Harald Kruggel-Emden Uwe D. Hanebeck Intelligent Sensor-Actuator-Systems Laboratory Karlsruhe Institute of Technology 76131 Karlsruhe Germany Chair of Mechanical Process Engineering and Solids Processing Technische Universität Berlin 10587 Berlin Germany Fraunhofer Institute of Optronics System Technologies and Image Exploitation 76131 Karlsruhe Germany

Optical sorters separate particles of different classes by first detecting them while they are transported, e.g., on a conveyor belt, and subsequently bursting out particles of undesired classes using compressed air nozzles. Currently, the most promising results are achieved by predictive tracking, a multitarget tracking approach based on extracted midpoints from area-scan camera images that analyzes the particles’ motion and activates the nozzles accordingly. However, predictive tracking requires expert knowledge for setup and preceding object detection. Moreover, particle shapes are only considered implicitly, and the need to solve an association problem rises the computational complexity of the algorithm. In this paper, we present GridSort, an image-based approach that forecasts the scene at the nozzle array using a convolutional long short-term memory neural network and subsequently extracts nozzle activations, thus circumventing the aforementioned weaknesses. We show how GridSort can be trained in an unsupervised fashion and evaluate it using a coupled discrete element–computational fluid dynamics simulation of an optical sorter. We compare our method with predictive tracking in terms of sorting accuracy and demonstrate that it is an easy-to-apply alternative while achieving state-of-the-art results.

关键词： Monitoring of product quality and control performance Neural networks in process control Machine learning methods and applications Artificial intelligence in mining, minerals and metals process monitoring and fault diagnosis

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