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IEEE Conference on Decision and control

作者： Lukas Schwenkel Johannes Köhler Matthias A. Müller Frank Allgöwer Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart Germany Institute of Automatic Control Leibniz University Hannover Hannover Germany

ISBN: (数字)9781728174471

ISBN: (纸本)9781728174488

In this work, we propose a tube-based model predictive control (MPC) scheme for state and input constrained linear systems that are subject to dynamic uncertainties de-scribed by integral quadratic constraints (IQCs). We extend the framework of verifying exponential decay rates with IQCs in order to derive an exponentially stable scalar system that bounds the error between the nominal prediction model and the actual unknown system. In the proposed MPC scheme, this error bounding system is predicted together with the nominal model to define the size of the tube. We prove that this scheme achieves robust constraint satisfaction and input-to-state stability, and we demonstrate the flexibility of dynamic tubes in a numerical example.

关键词： Uncertainty Electron tubes Predictive models Stability analysis Numerical stability Computational modeling Linear systems

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Data-driven Polytopic Output Synchronization of Heterogeneous Multi-agent systems from Noisy Data

arXiv

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arXiv 2023年

作者： Li, Yifei Liu, Wenjie Sun, Jian Wang, Gang Xie, Lihua Chen, Jie The National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology Beijing100081 China The Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China School of Electrical and Electronic Engineering Nanyang Technological University Singapore The Department of Control Science and Engineering Tongji University Shanghai201804 China

This paper proposes a novel approach to addressing the output synchronization problem in unknown heterogeneous multi-agent systems (MASs) using noisy data. Unlike existing studies that focus on noiseless data, we introduce a distributed data-driven controller that enables all heterogeneous followers to synchronize with a leader’s trajectory. To handle the noise in the state-input-output data, we develop a data-based polytopic representation for the MAS. We tackle the issue of infeasibility in the set of output regulator equations caused by the noise by seeking approximate solutions via constrained fitting error minimization. This method utilizes measured data and a noise-matrix polytope to ensure near-optimal output synchronization. Stability conditions in the form of data-dependent semidefinite programs are derived, providing stabilizing controller gains for each follower. The proposed distributed data-driven control protocol achieves near-optimal output synchronization by ensuring the convergence of the tracking error to a bounded polytope, with the polytope size positively correlated with the noise bound. Numerical tests validate the practical merits of the proposed data-driven design and theory. © 2023, CC BY.

关键词： Multi agent systems

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Hybrid Routing in VANETs Using OLSR and Q-Learning for Enhanced Performance

Hybrid Routing in VANETs Using OLSR and Q-Learning for Enhan...

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Wafa Akermi Nouha Alyaoui Awatef Benfradj Guiloufi Karim Chabir Computer Science and Telecommunications Department Higher Institute of Applied Science and Technology Gafsa University Gafsa Tunisia Laboratory of Modeling Analysis and Control of Systems (MACS) National Engineering School of Gabes (ENIG) Gabes University Gabes Tunisia Departement of Computer Engineering College of Computer Qassim University Buraidh Saudi Ababia

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

High node mobility, rapid topology changes provide specific challenges for vehicular ad hoc networks (VANETs), which have an immediate impact on the routing protocols' performance. Traditional approaches, like the Optimized Link State Routing (OLSR) protocol, provide proactive route management but fail to fully account for critical dynamic parameters like link stability, relative vehicle speed, node distance, and bandwidth availability. This work proposes a hybrid method combining OLSR with Q-learning to facilitate real-time adaptive routing. The model leverages dynamic metrics to proactively evaluate links while employing Q-learning to optimize routing decisions based on rewards computed from performance factors like delay, packet loss rate, and link duration. Simulation results demonstrate that our approach significantly outperforms classic OLSR. The improvements include reduced packet loss rates, increased average throughput, lower average latency, and a reduction in control overhead. These findings confirm that integrating dynamic metrics and adaptive learning effectively addresses the challenges posed by VANETs.

关键词： Q-learning Simulation Vehicular ad hoc networks Packet loss Routing Throughput Routing protocols Stability analysis Topology Vehicle dynamics

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Diversity and Suitability of the State-of-the-Art Wearable and Wireless EEG systems Review

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IEEE Journal of Biomedical and Health Informatics 2023年第8期27卷 3830-3843页

作者： He, Congying Chen, Yu-Yi Phang, Chun-Ren Stevenson, Cory Chen, I-Ping Jung, Tzyy-Ping Ko, Li-Wei Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Institute of Applied Arts National Yang Ming Chiao Tung University Hsinchu30010 Taiwan International Ph.D. Program in Interdisciplinary Neuroscience National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Institute for Neural Computation and Institute of Engineering in Medicine University of California San DiegoCA90093 United States National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Institute of Electrical and Control Engineering Department of Electronics and Electrical Engineering Department of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Department of Biomedical Science and Environment Biology Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung80708 Taiwan

Wireless electroencephalography (EEG) systems have been attracting increasing attention in recent times. Both the number of articles discussing wireless EEG and their proportion relative to general EEG publications have increased over years. These trends indicate that wireless EEG systems could be more accessible to researchers and the research community has recognized the potential of wireless EEG systems. To explore the development and diverse applications of wireless EEG systems, this review highlights the trends in wearable and wireless EEG systems over the past decade and compares the specifications and research applications of the major wireless systems marketed by 16 companies. For each product, five parameters (number of channels, sampling rate, cost, battery life, and resolution) were assessed for comparison. Currently, these wearable and portable wireless EEG systems have three main application areas: consumer, clinical, and research. To address this multitude of options, the article also discussed the thought process to find a suitable device that meets personalization and use cases specificities. These investigations suggest that low-price and convenience are key factors for consumer applications, wireless EEG systems with FDA or CE-certification may be more suitable for clinical settings, and devices that provide raw EEG data with high-density channels are important for laboratory research. This article presents an overview of the current state of the wireless EEG systems specifications and possible applications and serves as a guide point as it is expected that more influential and novel research will cyclically promote the development of such EEG systems. © 2023 IEEE.

关键词： Electroencephalography

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Active Wildfires Detection and Dynamic Escape Routes Planning for Humans Through Information Fusion between Drones and Satellites

Active Wildfires Detection and Dynamic Escape Routes Plannin...

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International Conference on Intelligent Transportation

作者： Chang Liu Tamas Sziranyi Department of Networked Systems and Services Budapest University of Technology and Economics Müegyetem rkp. 3 H-1111 Budapest Hungary and Machine Perception Research Laboratory of Institute for Computer Science and Control (SZTAKI) Budapest Hungary Faculty of Transportation Engineering and Vehicle Engineering Machine Perception Research Laboratory of Institute for Computer Science and Control (SZTAKI) Budapest University of Technology and Economics (BME-KJK) Müegyetem rkp. 3 H-1111 Budapest Hungary Budapest Hungary

UAVs are playing an increasingly important role in the field of wilderness rescue by virtue of their flexibility. This paper proposes a fusion of UAV vision technology and satellite image analysis technology for active wildfires detection and road networks extraction of wildfire areas and real-time dynamic escape route planning for people in distress. Firstly, the fire source location and the segmentation of smoke and flames are targeted based on Sentinel 2 satellite imagery. Secondly, the road segmentation and the road condition assessment are performed by D-linkNet and NDVI values in the central area of the fire source by UAV. Finally, the dynamic optimal route planning for humans in real time is performed by the weighted A* algorithm in the road network with the dynamic fire spread model. Taking the Chongqing wildfire on August 24, 2022, as a case study, the results demonstrate that the dynamic escape route planning algorithm can provide an optimal real-time navigation path for humans in the presence of fire through the information fusion of UAVs and satellites.

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Delivering Improved Care through Remote Health Monitoring systems by Using Microservices. Case Study: Fall Detection Encompassed into Connected Care

Delivering Improved Care through Remote Health Monitoring Sy...

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International Conference on control systems and Computer Science (CSCS)

作者： Marilena Ianculescu Adriana Alexandru Ionuţ-Emanuel Giura Ana-Mihaela Vasilevschi Communication Digital Applications and Systems Department National Institute for Research and Development in Informatics Bucharest Romania Doctoral School of Automatic Control and Computers University Politehnica of Bucharest Bucharest Romania Counselors Department National Institute for Research and Development in Informatics Târgovişte Romania Faculty of Electrical Engineering Electronics and Information Technology Târgovişte Romania Valahia University of Târgovişte Târgovişte Romania

Based on today’s modern technologies, patient care can be provided remotely, in a connected way, being, at the same time, personalized, patient-centered and proactive. Such an approach can be achieved using Remote Health Monitoring systems (RHMS). In case of elderly people, dramatic permanent deteriorations of their health status can be caused by falls. The seniors’ health and life style monitoring and the detection and/or prevention of falls can be done by such RHMS, an example being the RO-SmartAgeing system developed inside “Non-invasive Monitoring System and Health Assessment of the Elderly in a Smart Environment (RO-SmartAgeing)” research project. The paper presents the problem of using microservices for optimizing the architecture and functionalities of RO-SmartAgeing system, and the way in which the problems of ensuring the security of patient data can be solved.

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An iteration scheme with stability guarantees for proximity moving horizon estimation

An iteration scheme with stability guarantees for proximity ...

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European control Conference (ECC)

作者： Meriem Gharbi Christian Ebenbauer Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart

ISBN: (数字)9783907144022

ISBN: (纸本)9781728188133

In this paper, we propose and investigate an iteration scheme for proximity moving horizon state estimation of discrete-time linear systems subject to polytopic constraints. Based on a relaxed barrier function formulation of the underlying optimization problem, the state estimate is computed at each time instant after a limited number of optimization iterations. We establish sufficient conditions for the stability of the resulting estimation error. A simulation example demonstrates the computational efficiency of the proposed scheme and illustrates its satisfactory performance in comparison with fully converged proximity moving horizon estimators.

关键词： Optimization Stability analysis Estimation error Time measurement State estimation Current measurement

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Network Learning with Directional Sign Patterns

Network Learning with Directional Sign Patterns

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IEEE Conference on Decision and control

作者： Anqi Dong Can Chen Tryphon T. Georgiou Department of Mathematics Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden Department of Mathematics School of Data Science and Society University of North Carolina Chapel Hill Chapel Hill NC USA Department of Mechanical and Aerospace Engineering University of California Irvine CA USA

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Complex systems can be effectively modeled via graphs that encode networked interactions, where relations between entities or nodes are often quantified by signed edge weights, e.g., promotion/inhibition in gene regulatory networks, or encoding political of friendship differences in social networks. However, it is often the case that only an aggregate consequence of such edge weights that characterize relations may be directly observable, as in protein expression of in gene regulatory networks. Thus, learning edge weights poses a significant challenge that is further exacerbated for intricate and large-scale networks. In this article, we address a model problem to determine the strength of sign-indefinite relations that explain marginal distributions that constitute our data. To this end, we develop a paradigm akin to that of the Schrödinger bridge problem and an efficient Sinkhorn type algorithm (more properly, Schrödinger-Fortet-Sinkhorn algorithm) that allows fast convergence to parameters that minimize a relative entropy/likelihood criterion between the sought signed adjacency matrix and a prior. The formalism that we present represents a novel generalization of the earlier Schrödinger formalism in that marginal computations may incorporate weights that model directionality in underlying relations, and further, that it can be extended to high-order networks - the Schrödinger-Fortet-Sinkhorn algorithm that we derive is applicable all the same and allows geometric convergence to a sought sign-indefinite adjacency matrix or tensor, for high-order networks.

关键词： Proteins Maximum likelihood estimation Tensors Social networking (online) Computational modeling Encoding Data models Computational complexity Complex systems Convergence

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AdvDiffuser: Generating Adversarial Safety-Critical Driving Scenarios via Guided Diffusion

arXiv

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arXiv 2024年

作者： Xie, Yuting Guo, Xianda Wang, Cong Liu, Kunhua Chen, Long School of Computer Science and Engineering Sun Yat-Sen University China School of Computer Science Wuhan University China State Key Laboratory for Management and Control of Complex Systems The Institute of Automation Chinese Academy of Sciences China School of Mechanical and Automotive Engineering Qingdao University of Technology China

Safety-critical scenarios are infrequent in natural driving environments but hold significant importance for the training and testing of autonomous driving systems. The prevailing approach involves generating safety-critical scenarios automatically in simulation by introducing adversarial adjustments to natural environments. These adjustments are often tailored to specific tested systems, thereby disregarding their transferability across different systems. In this paper, we propose AdvDiffuser, an adversarial framework for generating safety-critical driving scenarios through guided diffusion. By incorporating a diffusion model to capture plausible collective behaviors of background vehicles and a lightweight guide model to effectively handle adversarial scenarios, AdvDiffuser facilitates transferability. Experimental results on the nuScenes dataset demonstrate that AdvDiffuser, trained on offline driving logs, can be applied to various tested systems with minimal warm-up episode data and outperform other existing methods in terms of realism, diversity, and adversarial performance. © 2024, CC BY.

关键词： automatic guided vehicles

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Rollout scheduling and control for disturbed systems via tube MPC

arXiv

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arXiv 2020年

作者： Wildhagen, Stefan Allgöwer, Frank Institute for Systems Theory and Automatic Control University of Stuttgart Germany

— Rollout control is an MPC-based control method, in which a controller is periodically activated to schedule the transmission of sensor or actuator data. Therein, a preassigned traffic specification acts as a constraint on the scheduled transmissions, ensuring that they are triggered at an admissible rate for the underlying communication network. In this paper, we extend the theory of rollout control by considering bounded disturbances on the controlled plant in the presence of state and input constraints. We use methods from tube MPC, where the error between the nominal (undisturbed) system, used as a prediction model, and the real system is kept in a robust control invariant set. This approach requires satisfaction of a maximum inter-transmission interval in closed loop, a guarantee that is not straightforward to obtain in rollout control. Our main contribution is to introduce a novel tube MPC scheme adapted for rollout control, which contains an additional constraint on the predicted transmission schedule. We show that by virtue of this schedule constraint, the inter-transmission interval is bounded in closed loop. We also establish recursive feasibility of this novel MPC scheme and show convergence of the system. Copyright © 2020, The Authors. All rights reserved.

关键词： Robust control

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