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Robust Event-Triggered control of Nonlinear Systems Under a Global Sector-Bound Condition

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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A Stackelberg Game Framework for Energy Internet System By Operator Approach

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IEEE Transactions on Network Science and engineering 2025年

作者： Chen, Yue Yi, Peng Lei, Jinlong Li, Xiangjun Tongji University Department of Control Science and Engineering Shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education China China Electric Power Research Institute National Key Laboratory of Renewable Energy Grid-Integration Energy Storage and Electrical Engineering Department Beijing100192 China

This paper proposes a Stackelberg game framework for managing an Energy Internet System that integrates renewable energy generation, energy conversion, and energy trading. The system comprises hubs controlled by competing energy companies, incorporating both external energy trading and peer-to-peer energy exchanges. It involves multiple stakeholders whose decisions are interdependent, creating challenges in decision-making. To tackle these challenges, we propose a networked Stackelberg game framework with two main objectives. First, from the energy companies' perspective, the companies make decisions by considering strategic interactions with other companies while accounting for the best responses of passive consumers within peer-to-peer constraints. Second, from the consumer side, consumers adjust their decisions based on their observations of the companies' strategies. The framework adopts a hierarchical decision-making structure in which energy companies act as leaders, formulating strategies that anticipate consumer demand responses, while competing within a Nash game. Meanwhile, consumer clusters, managed by demand management centers, modify their energy usage based on an incentive price mechanism. To search for the equilibrium, we develop an operator-theoretic approach that combines implicit gradient methods with proximal operator splitting techniques, and prove its convergence. Numerical studies and simulations on a combined IEEE 37-bus and gas source model with multiple energy hubs validate the model's effectiveness and the efficiency of the proposed algorithms. The results demonstrate the operational efficiency and strategic stability of the system, emphasizing the advantages of active market participation for both energy companies and consumers. © 2013 IEEE.

关键词： Demand response

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Multi-Target Tracker for Low Light Vision

Multi-Target Tracker for Low Light Vision

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International Conference on Advanced Robotics (ICAR)

作者： Nadya Abdel Madjid Arjun Sharma Bilal Hassan Naoufel Werghi Jorge Dias Majid Khonji Department of Electrical Engineering and Computer Science Center for Autonomous Robotic Systems (KUCARS) Khalifa University of Science and Technology Abu Dhabi UAE

Recently, remarkable progress has been achieved in addressing the problem of multi-object tracking (MOT), especially in the context of autonomous vehicles (AV). One of the prospective domains of MOT tracking is thermal infrared (TIR) tracking, which can equip an AV with the ability to track pedestrians and vehicles in low light conditions. In this paper, we propose a multi-object tracker for TIR images with a focus on simple and light-weight algorithmic solution. We base our solution on DeepSORT algorithm and extend it to TIR tracking of both pedestrians and vehicles. To adopt DeepSORT algorithm, we design an appearance descriptor suitable for the association problem for TIR images. Furthermore, to address the problem of missing association and detection, we propose a fusion block to merge short tracklets belonging to the same object in one track. We evaluate the tracker on CAMEL dataset and experimentally on the sequences we collected using an IR-camera. The tracker's code is available at ***/AV-Lab/IR_tracking.

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Distributed Coordinated Optimal control for Synchronous Operation of Virtually Coupled Train Set 27

Distributed Coordinated Optimal Control for Synchronous Oper...

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27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024

作者： Luo, Xiaolin Wang, Dongming Wang, Wei Ji, Yindong Liu, Hongjie Beijing Jiaotong University State Key Laboratory of Advanced Rail Autonomous Operation Beijing100044 China University of California Department of Electrical and Computer Engineering RiversideCA92521 United States Traffic Control Technology Co. Ltd Beijing100070 China Tsinghua University Department of Automation Beijing100084 China School of Automation and Intelligence Beijing Jiaotong University Beijing100044 China

ISBN: (纸本)9798331505929

Virtual coupling technologies have been widely studied in recent years, due to their merits of flexibility and efficiency. However, to operate a virtually coupled train set (VCTS) as a single train, the synchronous operation is still a critical problem to be addressed, especially in arriving. To this end, we propose a distributed coordinated optimal control (DCOC) approach integrated with distributed optimization and model predictive control. First, we formulate a globally coordinated optimal control problem for VCTS, where the states of units in VCTS are coupled in the cost and constraints. Then, we design a distributed algorithm to solve the global problem, where local problems are decoupled into ones with fewer dimensions. Next, we employ distributed model predictive control to guarantee the satisfaction of safety constraints before the convergence of the distributed algorithm. Finally, experimental results demonstrate that our approach can achieve stable and synchronous operation for VCTS and save by 90% computation time than existing centralized approaches. © 2024 IEEE.

关键词： Predictive control systems

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Distributed Online Bandit Nonconvex Optimization with One-Point Residual Feedback via Dynamic Regret

arXiv

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arXiv 2024年

作者： Hua, Youqing Liu, Shuai Hong, Yiguang Johansson, Karl Henrik Wang, Guangchen School of Control Science and Engineering Shandong University Jinan China Nanyang Technological University Singapore Department of Control Science and Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

This paper considers the distributed online bandit optimization problem with nonconvex loss functions over a time-varying digraph. This problem can be viewed as a repeated game between a group of online players and an adversary. At each round, each player selects a decision from the constraint set, and then the adversary assigns an arbitrary, possibly nonconvex, loss function to this player. Only the loss value at the current round, rather than the entire loss function or any other information (e.g. gradient), is privately revealed to the player. Players aim to minimize a sequence of global loss functions, which are the sum of local losses. We observe that traditional multi-point bandit algorithms are unsuitable for online optimization, where the data for the loss function are not all a priori, while the one-point bandit algorithms suffer from poor regret guarantees. To address these issues, we propose a novel one-point residual feedback distributed online algorithm. This algorithm estimates the gradient using residuals from two points, effectively reducing the regret bound while maintaining O(1) sampling complexity per iteration. We employ a rigorous metric, dynamic regret, to evaluate the algorithm's performance. By appropriately selecting the step size and smoothing parameters, we demonstrate that the expected dynamic regret of our algorithm is comparable to existing algorithms that use two-point feedback, provided the deviation in the objective function sequence and the path length of the minimization grows sublinearly. Finally, we validate the effectiveness of the proposed algorithm through numerical simulations. Copyright © 2024, The Authors. All rights reserved.

关键词： Optimization algorithms

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Unified Temporal Erasable Itemset Mining with a Lower-Bound Strategy

Unified Temporal Erasable Itemset Mining with a Lower-Bound ...

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2022 IEEE International Conference on Big Data, Big Data 2022

作者： Hong, Tzung-Pei Li, Jia-Xiang Tsai, Yu-Chuan Huang, Wei-Ming National University of Kaohsiung Department of Computer Science and Information Engineering Kaohsiung Taiwan National Sun Yat-Sen University Department of Computer Science and Engineering Kaohsiung Taiwan National University of Kaohsiung Library and Information Center Kaohsiung Taiwan China Steel Inc Department of Electrical and Control Kaohsiung Taiwan

ISBN: (纸本)9781665480451

Erasable itemset mining has been a valuable mining problem for manufacturers. It can extract less profitable materials from a product dataset and provide managers with good decision-making and a trade-off between cost and profit. However, the traditional erasable itemset mining methods seldom consider the time factor. For time-sensitive industries such as agro-processors, the time range is important in determining which materials are less profitable. Hong et al. first proposed the concept of temporal erasable itemset mining and seven lifespan options. They also proposed a unified temporal erasable (UTE) mining algorithm for getting incomplete temporal erasable itemsets. Howerever, the UTE algorithm does not satisfy the property of downward closure. In this work, we propose an improved algorithm to improve the performance of the UTE algorithm based on a lower-bound strategy and satisfying the property of downward closure. The proposed algorithm uses a hash table to store information that will be reused during the mining process to avoid scanning a dataset multiple times. The designed lower-bound strategy can preserve the downward closure property, narrowing the search space of candidate itemsets. In numerical experiments, we compare the performance using several metrics between the proposed method and the previous work. From the results of experiments, our proposed method outperforms the existing method on various metrics, such as execution time and the number of candidate erasable itemsets. © 2022 IEEE.

关键词： Data mining

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control-oriented modeling and passivity analysis of thermal dynamics in a multi-producer district heating system

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IFAC-PapersOnLine 2023年第1期56卷 175-180页

作者： Saeed Ahmed Juan E. Machado Michele Cucuzzella Jacquelien M.A. Scherpen Jan C. Willems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen 9747 AG Groningen The Netherlands Department of Electrical Computer and Biomedical Engineering University of Pavia Italy

Climate change and geopolitics have led to the conception of plans for reducing greenhouse gas emissions and improving the sustainability of existing fossil-based energy systems. In this respect, district heating has been identified as an indispensable player for its potential to integrate seamlessly environmentally-friendly heat sources. To improve the efficiency of these district heating systems, optimal operation schemes can be devised and enforced through control systems. To this end, we present a control-oriented nonlinear ODE-based model of temperature dynamics in a multi-producer district heating system. The model features a modular design and comprises the thermal dynamics of heat exchangers of producers and consumers interconnected by a distribution network of meshed topology. Then, we establish passivity properties and zero-state detectability for the modeled temperature dynamics that could be exploited for controller design and solving constrained optimization problems.

关键词： District heating thermal dynamics Krasovskii passivity shifted passivity zero-state detectability

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Development of a Modified Dummy Gas Lift Valve for Subsurface Depth-Resolved Microbiological Sampling and 3D Mapping

Development of a Modified Dummy Gas Lift Valve for Subsurfac...

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2024 SPE Water Lifecycle Management Conference and Exhibition, WLMC 2024

作者： McElhinney, J.M.W.R. Gomes, J.S. Hasan, A. Dias, J. BME Department Khalifa University Abu Dhabi United Arab Emirates Centre for Membranes and Advanced Water Technology Arzanah Building Khalifa University SAN Campus Abu Dhabi United Arab Emirates Computer and Electrical Engineering Dept. Khalifa University Abu Dhabi United Arab Emirates KU Center for Autonomous Robotic Systems

ISBN: (纸本)9781959025320

Objectives/Scope: This study outlines the development and use of a modified dummy gas lift valve designed to obtain subsurface microbiological samples from a defined depth series across a production well. An overview of the initial field pilot is presented wherein microbiological data from the modified valve will be contrasted with topside samples to evaluate the information yielded from sampling downhole biofilm communities in place of planktonic populations from the well head. Methods, Procedures, Process: In this approach, the modified dummy gas lift valve, preloaded topside with carbonate plugs and coupons, is deployed at various depths in the well's completion for downhole incubation. This modification allows production fluids to wet the payloads, enabling in situ biofilm colonization by reservoir communities across depth and temperature gradients. Post retrieval using a slickline tool, sample DNA is extracted for metagenomic sequencing, assessing microbial composition and metabolic capabilities (including souring and MIC-related activities). Concurrent production fluid samples from the wellhead will be analyzed for comparison to evaluate any information gained from biofilm over planktonic population sampling. Results, Observations, Conclusions: Samples from the modified valve are expected to provide sufficient yields of DNA, uncontaminated by non-resident microbes from outside of the producer. Microbial data from downhole biofilms is anticipated to provide a more diverse community makeup than production fluid communities sampled at the wellhead, with a corresponding increase in problematic species associated with MIC and souring. Corrosion coupon analyses will enable conclusions regarding proactive decision-making enablement and extrapolations of 3D projections of microbiological communities between modified valves across the completion column will provide the relationship between in situ conditions, microbial colonization in the context of pore space and risk

关键词： Decision making

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Hidden Convexity-Based Distributed Operation of Integrated Electricity-Gas Systems

arXiv

引用

arXiv 2024年

作者： Liu, Rong-Peng Song, Yue Liu, Junhong Wang, Xiaozhe Guo, Jinpeng Hou, Yunhe The Department of Electrical and Computer Engineering McGill University MontrealQCH3A 0E9 Canada The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai China The Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong The Department of Energy and Electrical Engineering Ho-Hai University Jiangsu Nanjing China

This letter proposes a hidden convexity-based method to address distributed optimal energy flow (OEF) problems for transmission-level integrated electricity-gas systems. First, we develop a node-wise decoupling method to decompose an OEF problem into multiple OEF subproblems. Then, we propose a hidden convexity-based method to equivalently reformulate nonconvex OEF subproblems as semi-definite programs. This method differs from any approximation and convexification methods that may incur infeasible solutions. Since all OEF subproblems are originally convex or equivalently convexified, we adopt an ADMM to solve the hidden convexity-based distributed OEF problem with convergence analysis. Test results validate the effectiveness of the proposed method, especially in handling a large number of agents. Copyright © 2024, The Authors. All rights reserved.

关键词： Quadratic programming

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Robust Multivariate Detection and Estimation with Fault Frequency Content Information

arXiv

引用

arXiv 2023年

作者： Dong, Jingwei Pan, Kaikai Pequito, Sérgio Esfahani, Peyman Mohajerin The Delft Center for Systems and Control Delft University of Technology Netherlands The College of Electrical Engineering Zhejiang University China The Department of Electrical and Computer Engineering University of Lisbon Lisbon Portugal

This paper studies the problem of fault detection and estimation (FDE) for linear time-invariant (LTI) systems with a particular focus on frequency content information of faults, possibly as multiple disjoint continuum ranges, and under both disturbances and stochastic noise. To ensure the worst-case fault sensitivity in the considered frequency ranges and mitigate the effects of disturbances and noise, an optimization framework incorporating a mixed H/H2 performance index is developed to compute the optimal detection filter. Moreover, a thresholding rule is proposed to guarantee both the false alarm rate (FAR) and the fault detection rate (FDR). Next, shifting attention to fault estimation in specific frequency ranges, an exact reformulation of the optimal estimation filter design using the restricted H∞ performance index is derived, which is inherently non-convex. However, focusing on finite frequency samples and fixed poles, a lower bound is established via a highly tractable quadratic programming (QP) problem. This lower bound together with an alternating optimization (AO) approach to the original estimation problem leads to a suboptimality gap for the overall estimation filter design. The effectiveness of the proposed approaches is validated through applications of a non-minimum phase hydraulic turbine system and a multi-area power system. Copyright © 2023, The Authors. All rights reserved.

关键词： Hydraulic motors

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