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arXiv 2021年

作者： Ye, Mengbin Anderson, Brian D.O. Janson, Axel Gracy, Sebin Johansson, Karl H. Centre for Optimisation and Decision Science Curtin University Perth Australia School of Engineering Australian National University Canberra Australia Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology and Digital Futures Stockholm Sweden Department of Electrical and Computer Engineering Rice University TX United States

We use a deterministic model to study two competing viruses spreading over a two-layer network in the Susceptible-Infected-Susceptible (SIS) framework, and address a central problem of identifying the winning virus in a "survival-of-the-fittest" battle. Existing sufficient conditions ensure that the same virus always wins regardless of initial states. For networks with an arbitrary but finite number of nodes, there exists a necessary and sufficient condition that guarantees local exponential stability of the two equilibria corresponding to each virus winning the battle, meaning that either of the viruses can win, depending on the initial states. However, establishing existence and finding examples of networks with more than three nodes that satisfy such a condition has remained unaddressed. In this paper, we address both issues for networks with an arbitrary but finite number of nodes. We do this by proving that given almost any network layer of one virus, there exists a network layer for the other virus such that the resulting two-layer network satisfies the aforementioned condition. To operationalize our findings, a four-step procedure is developed to reliably and consistently design one of the network layers, when given the other layer. Conclusions from numerical case studies, including a real-world mobility network that captures the commuting patterns for people between 107 provinces in Italy, extend on the theoretical result and its consequences. Copyright © 2021, The Authors. All rights reserved.

关键词： Viruses

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Identifying 3D genome organization in diploid organisms via euclidean distance geometry

arXiv

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arXiv 2021年

作者： Belyaeva, Anastasiya Kubjas, Kaie Sun, Lawrence J. Uhler, Caroline Laboratory for Information and Decision Systems Department of Electrical Engineering and Computer Science Institute for Data Systems and Society Massachusetts Institute of Technology CambridgeMA United States Department of Mathematics and Systems Analysis Aalto University Espoo Finland

The spatial organization of the DNA in the cell nucleus plays an important role for gene regulation, DNA replication, and genomic integrity. Through the development of chromosome conformation capture experiments (such as 3C, 4C, Hi-C) it is now possible to obtain the contact frequencies of the DNA at the whole-genome level. In this paper, we study the problem of reconstructing the 3D organization of the genome from such whole-genome contact frequencies. A standard approach is to transform the contact frequencies into noisy distance measurements and then apply semidefinite programming (SDP) formulations to obtain the 3D configuration. However, neglected in such reconstructions is the fact that most eukaryotes including humans are diploid and therefore contain two copies of each genomic locus. We prove that the 3D organization of the DNA is not identifiable from distance measurements derived from contact frequencies in diploid organisms. In fact, there are infinitely many solutions even in the noise-free setting. We then discuss various additional biologically relevant and experimentally measurable constraints (including distances between neighboring genomic loci and higher-order interactions) and prove identifiability under these conditions. Furthermore, we provide SDP formulations for computing the 3D embedding of the DNA with these additional constraints and show that we can recover the true 3D embedding with high accuracy from both noiseless and noisy measurements. Finally, we apply our algorithm to real pairwise and higher-order contact frequency data and show that we can recover known genome organization patterns. © 2021, CC BY.

关键词： DNA

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Toolbox for Discovering Dynamic System Relations via TAG Guided Genetic Programming

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IFAC-PapersOnLine 2021年第7期54卷 379-384页

作者： Ştefan-Cristian Nechita Roland Tóth Dhruv Khandelwal Maarten Schoukens Department of Electrical Engineering Eindhoven University of Technology Eindhoven University of Technology Eindhoven The Netherlands Systems and Control Laboratory Institute for Computer Science and Control Kende u. 13-17 H-1111 Budapest Hungary

Data-driven modeling of nonlinear dynamical systems often requires an expert user to take critical decisions a priori to the identification procedure. Recently, an automated strategy for data driven modeling of single-input single-output (SISO) nonlinear dynamical systems based on genetic programming (GP) and tree adjoining grammars (TAG) was introduced. The current paper extends these latest findings by proposing a multi-input multi-output (MIMO) TAG modeling framework for polynomial NARMAX models. Moreover, we introduce a TAG identification toolbox in Matlab that provides implementation of the proposed methodology to solve multi-input multi-output identification problems under NARMAX noise assumption. The capabilities of the toolbox and the modeling methodology are demonstrated in the identification of two SISO and one MIMO nonlinear dynamical benchmark models.

关键词： Nonlinear system identification Equation discovery Tree Adjoining Grammar Genetic Programming Data-driven system modeling

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Short - Term Prediction of Coke Pushing Current Peak Based on Improved ARIMA Model

Short - Term Prediction of Coke Pushing Current Peak Based o...

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Industrial Cyber-Physical systems (ICPS)

作者： Haiyang Wei Luefeng Chen Jie Hu Yi Ren Min Wu Witold Pedrycz Kaoru Hirota School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada Tokyo Institute of Technology Yokohama Japan

Coke pushing current is an indicator to evaluate the difficulty of coke pushing operation. The higher coke pushing current is, the greater coke pushing resistance is, and the more difficult coke is to push out. Accurate prediction of current peak during future coke pushing operation can provide more time for production personnel to adjust production status and avoid difficult coke pushing in carbonization chamber. In this paper, a combination prediction model based on VMD (Variational Mode Decomposition) and improved ARIMA (Autoregressive Integrated Moving Average) models is proposed. Firstly, VMD algorithm is used to decompose time series of coke pushing current peak, de-noising data, and extracting main information of time series. Then, ARIMA model is used to predict mean change of linear elasticity and GARCH (Generalized Autore-gressive Conditional Heteroskedasticity) model is introduced to predict ARIMA model residual and improve heteroscedasticity of nonlinear part of time series, and then ARIMA-GARCH model is established. Finally, predicted value is obtained by the sum of each component prediction. The experimental results show that the proposed prediction model has a high prediction accuracy in the short-term prediction of coke pushing current peak. The scheme is applied to actual coking production to guide production of coke.

关键词： Resistance Ovens Time series analysis Noise reduction Production Predictive models Prediction algorithms

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Active Simultaneously Transmitting and Reflecting Surface Assisted NOMA Networks

arXiv

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arXiv 2024年

作者： Yue, Xinwei Xie, Jin Ouyang, Chongjun Liu, Yuanwei Shen, Xia Ding, Zhiguo The Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing100101 China The Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China The School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom Beijing100191 China The Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi United Arab Emirates Department of Electrical Engineering Princeton University Princeton United States

The novel active simultaneously transmitting and reflecting surface (ASTARS) has recently received a lot of attention due to its capability to conquer the multiplicative fading loss and achieve full-space smart radio environments. This paper introduces the ASTARS to assist non-orthogonal multiple access (NOMA) communications, where the stochastic geometry theory is used to model the spatial positions of pairing users. We design the independent reflection/transmission phase-shift controllers of ASTARS to align the phases of cascaded channels at pairing users. We derive new closed-form and asymptotic expressions of the outage probability and ergodic data rate for ASTARS-NOMA networks in the presence of perfect/imperfect successive interference cancellation (pSIC). The diversity orders and multiplexing gains for ASTARS-NOMA are derived to provide more insights. Furthermore, the system throughputs of ASTARS-NOMA are investigated in both delay-tolerant and delay-limited transmission modes. The numerical results are presented and show that: 1) ASTARS-NOMA with pSIC outperforms ASTARS assisted-orthogonal multiple access (ASTARS-OMA) in terms of outage probability and ergodic data rate;2) The outage probability of ASTARS-NOMA can be further reduced within a certain range by increasing the power amplification factors;3) The system throughputs of ASTARS-NOMA are superior to that of ASTARS-OMA in both delay-limited and delay-tolerant transmission modes. Copyright © 2024, The Authors. All rights reserved.

关键词： Stochastic systems

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Finite time exact quantized average consensus with limited resources and transmission stopping for energy-aware networks

arXiv

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arXiv 2021年

作者： Rikos, Apostolos I. Hadjicostis, Christoforos N. Johansson, Karl H. Division of Decision and Control Systems KTH Royal Institute of Technology Digital Futures StockholmSE-100 44 Sweden Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus

Composed of spatially distributed sensors and actuators that communicate through wireless networks, networked control systems are emerging as a fundamental infrastructure technology in 5G and IoT technologies, including diverse applications, such as autonomous vehicles, UAVs, and various sensing devices. In order to increase flexibility and reduce deployment and maintenance costs, many such applications consider battery-powered or energy-harvesting networks, which bring additional limitations on the energy consumption of the wireless network. Specifically, the operation of battery-powered or energy-harvesting wireless communication networks needs to guarantee (i) efficient communication between nodes and (ii) preservation of available energy. Motivated by these novel requirements, in this paper, we present and analyze a novel distributed average consensus algorithm, which (i) operates exclusively on quantized values (in order to guarantee efficient communication and data storage), and (ii) relies on event-driven updates (in order to reduce energy consumption, communication bandwidth, network congestion, and/or processor usage). We characterize the properties of the proposed algorithm and show that its execution, on any time-invariant and strongly connected digraph, will allow all nodes to reach, in finite time, a common consensus value that is equal to the exact average (represented as the ratio of two quantized values). Furthermore, we show that our algorithm allows each node to cease transmissions once the exact average of the initial quantized values has been reached (in order to preserve its battery energy). Then, we present upper bounds on (i) the number of transmissions and computations each node has to perform during the execution of the algorithm, and (ii) the memory and energy requirements of each node in order for the algorithm to be executed. Finally, we provide examples that demonstrate the operation, performance, and potential advantages of our proposed

关键词： Multi agent systems

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Topological entropy of switched nonlinear and interconnected systems

arXiv

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arXiv 2023年

作者： Yang, Guosong Liberzon, Daniel Hespanha, João P. The Department of Electrical and Computer Engineering Rutgers University PiscatawayNJ08854 United States The Coordinated Science Laboratory University of Illinois Urbana-Champaign UrbanaIL61801 United States The Center for Control Dynamical Systems and Computation University of California Santa Barbara Santa BarbaraCA93106 United States

A general upper bound for topological entropy of switched nonlinear systems is constructed, using an asymptotic average of upper limits of the matrix measures of Jacobian matrices of strongly persistent individual modes, weighted by their active rates. A general lower bound is constructed as well, using a similar weighted average of lower limits of the traces of these Jacobian matrices. In a case of interconnected structure, the general upper bound is readily applied to derive upper bounds for entropy that depend only on "network-level" information. In a case of block-diagonal structure, less conservative upper and lower bounds for entropy are constructed. In each case, upper bounds for entropy that require less information about the switching signal are also derived. The upper bounds for entropy and their relations are illustrated by numerical examples of a switched Lotka–Volterra ecosystem *** Codes 37B40, 93C30 (Primary) 93C57 (Secondary) © 2023, CC BY-NC-ND.

关键词： Jacobian matrices

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Compositional Synthesis of Signal Temporal Logic Tasks via Assume-Guarantee Contracts

Compositional Synthesis of Signal Temporal Logic Tasks via A...

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IEEE Conference on decision and control

作者： Siyuan Liu Adnane Saoud Pushpak Jagtap Dimos V. Dimarogonas Majid Zamani Department of Electrical and Computer Engineering Technical University of Munich Germany Computer Science Department LMU Munich Germany Laboratoire des Signaux et Systèmes CentraleSupélec Univ. Paris Saclay France Robert Bosch Center for Cyber-Physical Systems in Indian Institute of Science Bangalore India Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden Computer Science Department University of Colorado Boulder USA

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

In this paper, we focus on the problem of compositional synthesis of controllers enforcing signal temporal logic (STL) tasks over a class of continuous-time nonlinear interconnected systems. By leveraging the idea of funnel-based control, we show that a fragment of STL specifications can be formulated as assume-guarantee contracts. A new concept of contract satisfaction is then defined to establish our compositionality result, which allows us to guarantee the satisfaction of a global contract by the interconnected system when all subsystems satisfy their local contracts. Based on this compositional framework, we then design closed-form continuous-time feedback controllers to enforce local contracts over subsystems in a decentralized manner. Finally, we demonstrate the effectiveness of our results on a numerical example.

关键词： Interconnected systems Task analysis Adaptive control Contracts

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On the convergence of step decay step-size for stochastic optimization

arXiv

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arXiv 2021年

作者： Wang, Xiaoyu Magnússon, Sindri Johansson, Mikael The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden Department of Computer and System Science Stockholm University Stockholm Sweden

The convergence of stochastic gradient descent is highly dependent on the step-size, especially on non-convex problems such as neural network training. Step decay step-size schedules (constant and then cut) are widely used in practice because of their excellent convergence and generalization qualities, but their theoretical properties are not yet well understood. We provide the convergence results for step decay in the non-convex regime, ensuring that the gradient norm vanishes at an (Formula presented) rate. We also provide the convergence guarantees for general (possibly non-smooth) convex problems, ensuring an (Formula presented) convergence rate. Finally, in the strongly convex case, we establish an (Formula presented) rate for smooth problems, which we also prove to be tight, and an (Formula presented) rate without the smoothness assumption. We illustrate the practical efficiency of the step decay step-size in several large scale deep neural network training tasks. Copyright © 2021, The Authors. All rights reserved.

关键词： Deep neural networks

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Dexterous Manipulation through Imitation Learning: A Survey

arXiv

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arXiv 2025年

作者： An, Shan Meng, Ziyu Tang, Chao Zhou, Yuning Liu, Tengyu Ding, Fangqiang Zhang, Shufang Mu, Yao Song, Ran Zhang, Wei Hou, Zeng-Guang Zhang, Hong School of Electrical and Information Engineering Tianjin University Tianjin300072 China School of Control Science and Engineering Shandong University Jinan250061 China State Key Laboratory of General Artificial Intelligence Beijing100086 China Department of Mechanical and Process Engineering ETH Zurich Zurich8092 Switzerland Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen518055 China School of Informatics University of Edinburgh EH8 9AB United Kingdom Department of Computer Science University of Hong Kong 999077 Hong Kong State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China CASIA-MUST Joint Laboratory of Intelligence Science and Technology Institute of Systems Engineering Macau University of Science and Technology 999078 China

Dexterous manipulation, which refers to the ability of a robotic hand or multi-fingered end-effector to skillfully control, reorient, and manipulate objects through precise, coordinated finger movements and adaptive force modulation, enables complex interactions similar to human hand dexterity. With recent advances in robotics and machine learning, there is a growing demand for these systems to operate in complex and unstructured environments. Traditional model-based approaches struggle to generalize across tasks and object variations due to the high-dimensionality and complex contact dynamics of dexterous manipulation. Although model-free methods such as reinforcement learning (RL) show promise, they require extensive training, large-scale interaction data, and carefully designed rewards for stability and effectiveness. Imitation learning (IL) offers an alternative by allowing robots to acquire dexterous manipulation skills directly from expert demonstrations, capturing fine-grained coordination and contact dynamics while bypassing the need for explicit modeling and large-scale trial-and-error. This survey provides an overview of dexterous manipulation methods based on imitation learning (IL), details recent advances, and addresses key challenges in the field. Additionally, it explores potential research directions to enhance IL-driven dexterous manipulation. Our goal is to offer researchers and practitioners a comprehensive introduction to this rapidly evolving domain. Copyright © 2025, The Authors. All rights reserved.

关键词： Grippers

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