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arXiv 2024年

作者： Jindal, Ashutosh Nicolau, Florentina Diego, David Martín Banavar, Ravi Systems and Control Engineering Indian Institute of Technology Bombay Maharashtra Mumbai400076 India Quartz EA7393 École Nationale Supérieure de l’Électronique et de ses Applications Cergy France Calle Nicolás Cabrera 13-15 Madrid28049 Spain

Dynamic feedback linearization-based methods allow us to design control algorithms for a fairly large class of nonlinear systems in continuous time. However, this feature does not extend to their sampled counterparts, i.e., for a given dynamically feedback linearizable continuous time system, its numerical discretization may fail to be so. In this article, we present a way to construct discretization schemes (accurate up to first order) that result in schemes that are feedback linearizable. This result is an extension of our previous work, where we had considered only static feedback linearizable systems. The result presented here applies to a fairly general class of nonlinear systems, in particular, our analysis applies to both endogenous and exogenous types of feedback. While the results in this article are presented on a control affine form of nonlinear systems, they can be readily modified to general nonlinear systems. © 2024, CC BY.

关键词： Nonlinear systems

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Digital Twin-based Cyber-Attack Detection Framework for Cyber-Physical Manufacturing systems

TechRxiv

引用

TechRxiv 2022年

作者： Balta, Efe C. Pease, Michael Moyne, James Barton, Kira Tilbury, Dawn M. The Automatic Control Laboratory ETH Zurich Zurich8092 Switzerland The National Institute of Standards and Technology GaithersburgMD20899 United States The Department of Mechanical Engineering University of Michigan Ann ArborMI48109 United States

Smart manufacturing (SM) systems utilize run-time data to improve productivity via intelligent decision-making and analysis mechanisms on both machine and system levels. The increased adoption of cyber-physical systems in SM leads to the comprehensive framework of cyber-physical manufacturing systems (CPMS) where data-enabled decision-making mechanisms are coupled with cyber-physical resources on the plant floor. Due to their cyber-physical nature, CPMS are susceptible to cyber-attacks that may cause harm to the manufacturing system, products, or even the human workers involved in this context. Therefore, detecting cyber-attacks efficiently and timely is a crucial step towards implementing and securing high-performance CPMS in practice. This paper addresses two key challenges to CPMS cyber-attack detection. The first challenge is distinguishing expected anomalies in the system from cyber-attacks. The second challenge is the identification of cyber-attacks during transient response of CPMS due to closed-loop controllers. Digital twin (DT) technology emerges as a promising solution for providing additional insights into the physical process (twin) by leveraging run-time data, models, and analytics. In this work, we propose a DT framework for detecting cyber-attacks in CPMS during controlled transient behavior as well as expected anomalies of the physical process. We present a DT framework and provide details on structuring the architecture to support cyber-attack detection. Additionally, we present an experimental case study on off-the-shelf 3D printers to detect cyber-attacks utilizing the proposed DT framework to illustrate the effectiveness of our proposed approach. © 2022, CC BY.

关键词： Data Analytics

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Continuous agent-based modeling of adult-child pairs based on a pseudo-energy: relevance for public safety and egress efficiency

arXiv

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arXiv 2024年

作者： Xie, Chuan-Zhi Tang, Tie-Qiao Nicolas, Alexandre School of Transportation Science and Engineering Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beihang University Beijing100191 China Université Claude Bernard Lyon 1 CNRS Institut Lumière Matière VilleurbanneF-69622 France School of Management and Economics Beijing Institute of Technology China Yangtze Delta Region Academy Beijing Institute of Technology China

Pushes, falls, stampedes, and crushes are safety hazards that emerge from the collective motion of crowds, but might be avoided by better design and guidance. While pedestrian dynamics are now getting better understood on the whole, complex heterogeneous flows involving e.g. adult-child pairs, though widely found at e.g. crowded Chinese training schools, still defy the current understanding and capabilities of crowd simulation models. We substantially extend a recent agent-based model in which each agent’s choice of motion results from the minimization of a sum of intuitive contributions, in order to integrate adult-child pairs. This is achieved by adding a suitably defined pairing potential. The resulting model captures the relative positions of pair members in a quantitative fashion, as confirmed by small-scale controlled experiments, and also succeeds in describing collision avoidance between pairs. The model is used to simulate mixed adult-child flows at a T-junction and test the sensitivity to the design and pairing strategies. Simulation shows that making the post-confluence corridor wide enough is critical to avoid friction in the flow, and that tight hand-holding is advisable for safer evacuations (whereas more loosely bound pairs get split at high density) and, more marginally, more efficient egresses in normal conditions. Copyright © 2024, The Authors. All rights reserved.

关键词： Digital elevation model

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A Novel YJQR-LSTM Model for Nonparametric Probabilistic Sustainable Agriculture Wind Power Forecasting Based on Intelligent IoT

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IEEE Internet of Things Journal 2024年

作者： Wang, Jie Jiang, Junhui Chen, Xinlong Cai, Defu Wu, Yue Lu, Renzhi School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Harbin Engineering University College of Computer Science and Technology Harbin150001 China State Grid Hubei Electric Power Research Institute Hubei Wuhan430079 China School of Technology State Key Laboratory of Efficient Production of Forest Resources Key Laboratory of National Forestry and Grassland Administration on Forestry Equipment and Automation Beijing Forestry University Beijing100083 China Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing400065 China State Key Laboratory of Mechanical Transmission for Advanced Equipment Chongqing University Chongqing400044 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

Energy costs associated with the consumption of non-renewable energy sources have become an important issue in improving the international competitiveness of agriculture. Wind power, as a renewable energy source, can replace non-renewable energy sources to reduce energy costs and improve the sustainability of agricultural. However, the inherent intermittency, randomness, and volatility within weather conditions and wind speed presents a substantial challenge in accurately predicting wind power generation. This work proposes a novel YJQR-LSTM algorithm that leverages Yeo-Johnson quantile regression (YJQR) with a long short-term memory (LSTM) network for nonparametric probabilistic forecasting of wind power generation via the Intelligent Internet of Things. First, an improved YJQR model based on the YJ transformation is designed to obtain a more precise characterization of wind uncertainty, providing a more flexible probability density function for wind power generation. Then, utilizing the unique structure of the LSTM network to learn the parameters of the YJQR model, temporal features can be extracted from time series data. To mitigate the impact of outliers in the raw data on accuracy and improve computational efficiency, a novel logarithmic likelihood function is developed as the loss function utilized in the training phase. The effectiveness of the proposed algorithm is validated using a real-world dataset from five wind farms from the Global Energy Forecasting Competition. Numerical results demonstrate that the algorithm provides more accurate wind power prediction results in complex wind power data environments, which is important for making full use of wind energy and thus reducing the consumption of non-renewable energy in agriculture. © 2024 IEEE.

关键词： Wind forecasting

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Longitudinal control for Autonomous Racing with Combustion Engine Vehicles

arXiv

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arXiv 2025年

作者： Pitschi, Phillip Sagmeister, Simon Goblirsch, Sven Lienkamp, Markus Lohmann, Boris Technical University of Munich School of Engineering & Design Department of Engineering Physics and Computation Institute of Automatic Control Germany Technical University of Munich School of Engineering & Design Department of Mobility Systems Engineering Institute of Automotive Technology Germany

Usually, a controller for path- or trajectory tracking is employed in autonomous driving. Typically, these controllers generate high-level commands like longitudinal acceleration or force. However, vehicles with combustion engines expect different actuation inputs. This paper proposes a longitudinal control concept that translates high-level trajectory-tracking commands to the required low-level vehicle commands such as throttle, brake pressure and a desired gear. We chose a modular structure to easily integrate different trajectory-tracking control algorithms and vehicles. The proposed control concept enables a close tracking of the high-level control command. An anti-lock braking system, traction control, and brake warmup control also ensure a safe operation during real-world tests. We provide experimental validation of our concept using real world data with longitudinal accelerations reaching up to 25 sm2 . The experiments were conducted using the EAV24 racecar during the first event of the Abu Dhabi Autonomous Racing League on the Yas Marina Formula 1 Circuit. Copyright © 2025, The Authors. All rights reserved.

关键词： Traction control

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Model-based injector deposit detection 1

引用

14. Internationale MTZ-Fachtagung Großmotoren, 2019

作者： Hinrichs, Michael Isermann, Rolf Pickel, Peter European Technology Innovation Center John Deere Kaiserslautern67657 Germany Institute of Automatic Control TU Darmstadt Darmstadt64283 Germany

ISBN: (数字)9783658313715

ISBN: (纸本)9783658313708

Solenoid coil injectors are widely spread in the agricultural and heavyduty vehicle sector. These types are installed due to their higher development status, longer service life and robustness. Nevertheless, injector problems are one of the more frequent causes of malfunctions and failures in diesel combustion engines. Due to ever smaller diameters and more precise coordination of the individual components, injector deposits can have a major influence on the function of injectors. Deposits change the injected fuel mass, the emissions and the reliability of the engine. Reliability is the by far the most important customer requirement of commercial machinery. Especially internal deposits can lead to a complete failure of the engine. For example, the injector can stick in closed or even in open position and may cause engine damage. This paper presents a method for detecting internal and external deposits in the injector. The basis for the detection method is a high sampling rate of the rail pressure sensor. The results allow a qualitative statement about the injector condition. Internal and external deposits can be distinguished. If the deposits are too big, a service recommendation for injector replacement is issued. © Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2020.

关键词： Predictive maintenance

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An Efficient Adaptive Hierarchical Sliding Mode control Strategy Using Neural Networks for 3D Overhead Cranes

引用

International Journal of Automation and computing 2019年第5期16卷 614-627页

作者： Viet-Anh Le Hai-Xuan Le Linh Nguyen Minh-Xuan Phan Department of Automatic Control Hanoi University of Science and TechnologyHanoi 10000Vietnam Centre for Autonomous Systems University of Technology SydneyNew South Wales 2007Australia

In this paper, a new adaptive hierarchical sliding mode control scheme for a 3D overhead crane system is proposed. A controller is first designed by the use of a hierarchical structure of two first-order sliding surfaces represented by two actuated and un-actuated subsystems in the bridge crane. Parameters of the controller are then intelligently estimated, where uncertain parameters due to disturbances in the 3D overhead crane dynamic model are proposed to be represented by radial basis function networks whose weights are derived from a Lyapunov function. The proposed approach allows the crane system to be robust under uncertainty conditions in which some uncertain and unknown parameters are highly difficult to determine. Moreover, stability of the sliding surfaces is proved to be guaranteed. Effectiveness of the proposed approach is then demonstrated by implementing the algorithm in both synthetic and reallife systems, where the results obtained by our method are highly promising.

关键词： 3D overhead crane adaptive control hierarchical sliding mode control neural network radial basis function

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Interaction between Double Solitons in Anti-Pt Symmetric Synthetic Photonic Lattices

SSRN

引用

SSRN 2022年

作者： Yue, Yazhou Li, Jun Zhang, Zhiqing Gao, Tianxiang Wen, Zengrun Wang, Haohao Qi, Xinyuan Flight Automatic Control Research Institute Xi’an710065 China National Key Laboratory of Science and Technology on Aircraft Control Xi’an710065 China School of Physics Northwest University Xi’an710127 China Shandong Provincial Key Laboratory of Optics and Photonic Devices College of Physics and Electronics Shandong Normal University Jinan250014 China

An anti-parity-time symmetry (anti-PT symmetric) double fiber loop synthetic photonic lattice is constructed theoretically by projecting the intensity of two loops and adjusting the phase and gain/loss distribution. Numerical studies on pulse dynamics show that the trajectories of double-pulse solitons may be maniputlated by tuning the initial relative phases, pulse separation, nonlinearity, and non-Hermitian characteristics of the system. Our research may provide a new way to realize logic gate devices and optical switches in optical interconnection and optical communications. © 2022, The Authors. All rights reserved.

关键词： Optical lattices

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Tracing Intricate Cues in Dialogue: Joint Graph Structure and Sentiment Dynamics for Multimodal Emotion Recognition

arXiv

引用

arXiv 2024年

作者： Li, Jiang Wang, Xiaoping Zeng, Zhigang The School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The Institute of Artificial Intelligence Huazhong University of Science and Technology Wuhan430074 China The Hubei Key Laboratory of Brain-Inspired Intelligent Systems Huazhong University of Science and Technology Wuhan430074 China The Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Ministry of Education Wuhan430074 China

Multimodal emotion recognition in conversation (MERC) has garnered substantial research attention recently. Existing MERC methods face several challenges: (1) they fail to fully harness direct inter-modal cues, possibly leading to less-than-thorough cross-modal modeling;(2) they concurrently extract information from the same and different modalities at each network layer, potentially triggering conflicts from the fusion of multi-source data;(3) they lack the agility required to detect dynamic sentimental changes, perhaps resulting in inaccurate classification of utterances with abrupt sentiment shifts. To address these issues, a novel approach named GraphSmile is proposed for tracking intricate emotional cues in multimodal dialogues. GraphSmile comprises two key components, i.e., GSF and SDP modules. GSF ingeniously leverages graph structures to alternately assimilate inter-modal and intra-modal emotional dependencies layer by layer, adequately capturing cross-modal cues while effectively circumventing fusion conflicts. SDP is an auxiliary task to explicitly delineate the sentiment dynamics between utterances, promoting the model’s ability to distinguish sentimental discrepancies. Furthermore, GraphSmile is effortlessly applied to multimodal sentiment analysis in conversation (MSAC), forging a unified multimodal affective model capable of executing MERC and MSAC tasks. Empirical results on multiple benchmarks demonstrate that GraphSmile can handle complex emotional and sentimental patterns, significantly outperforming baseline models. Copyright © 2024, The Authors. All rights reserved.

关键词： Emotion Recognition

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Multi-Objective Optimization for Online Train Trajectory Planning with Moving Window Method

IAENG International Journal of Computer Science

引用

IAENG International Journal of Computer Science 2023年第3期50卷

作者： He, Zhiyu Li, Yinan Li, Hui Xu, Ning Communication & Signal Research Institute China Academy of Railway Sciences Corporation Limited Beijing100081 China Automatic Train Control Department Communication & Signal Research Institute China Academy of Railway Sciences Corporation Limited Beijing100081 China Communication & Signal Research Institute China Academy of Railway Sciences Corporation Limited Beijing100081 China Technology & Information Department Communication & Signal Research Institute China Academy of Railway Sciences Corporation Limited Beijing100081 China

Optimization on trajectory planning is significant offering the driver or automatic train operation system a guidance to drive the train efficiently. An optimal trajectory is subject to operational, geographic, physical and dynamic constraints. In previous studies, researchers have put much effort into offline optimization. However, operational errors in real situation are rarely taken into consideration. Thus, this paper proposes a dynamic trajectory planning to address the deviation. Specifically, first, we design an online optimization framework to display model predictive control-based train trajectory planning theory. Various constraints are set for optimization problem. Second, taking energy consumption and punctuality into consideration, we propose a moving window method to search the optimal variables, which are applied to evaluate the fitness function. Plus, to improve global search ability and convergence rate, we present a multi-swarm particle swarm optimization by dividing the population into several parts. On the basis of operational time error at reallocation positions, we design a novel weight allocation mechanism for the revaluation of fitness function. At last, taking real data from Beijing-Shanghai high-speed railway as an example, the robustness and effectiveness of the proposed algorithm is proved by comparing multiple parameters with some numerical results of simulations. The results show that the proposed method can adjust operating strategy dynamically so that the train runs in an energy-efficient way. Additionally, in delay scene, the proposed method can also guide the train to catch up with the scheduled time and save energy consumption. © (2023), (International Association of Engineers). All Rights Reserved.

关键词： Multiobjective optimization

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