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arXiv 2023年

作者： Spin, L.M. Verhoek, C. Heemels, W.P.M.H. Van De Wouw, N. Tóth, R. The Control Systems Group Eindhoven University of Technology Netherlands The Institute for Computer Science and Control Budapest Hungary The Control Systems Technology Group Eindhoven University of Technology Netherlands The Dynamics and Control Group Eindhoven University of Technology Netherlands

In this paper, we present a novel approach to combine data-driven non-parametric representations with model-based representations of dynamical systems. Based on a data-driven form of linear fractional transformations, we introduce a data-driven form of generalized plants. This form can be leveraged to accomplish performance characterizations, e.g., in the form of a mixed-sensitivity approach, and LMI-based conditions to verify finite-horizon dissipativity. In particular, we show how finite-horizon 2-gain under weighting filter-based general performance specifications are verified for implemented controllers on systems for which only input-output data is available. The overall effectiveness of the proposed method is demonstrated by simulation examples. © 2023, CC BY-NC-SA.

关键词： Dynamical systems

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Design of a Scheme for Failover of Large Screen Visualization System Graphic Workstation 4

Design of a Scheme for Failover of Large Screen Visualizatio...

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4th International Conference on Computer Engineering and Application, ICCEA 2023

作者： Ben, Hailong Peng, Qu Zhang, Xin Yang, Huafei Gao, Ruohan Wang, Lichen Shen, Chao Dai, Chenxing Nari Technology Nanjing Control Systems Co. Ltd. Nari Group Co.Ltd of China Jiangsu Nanjing China

ISBN: (纸本)9798350347548

In the architecture of large screen display system, the graphic workstation is mainly used as the carrier to project the display content on the graphic workstation to the large screen through the splicing controller. When the graphic workstation fails, it will directly affect the display content and effect of the large screen. This paper proposes a disaster recovery scheme for the graphic workstation that is most prone to failure in the large screen system architecture. When the graphic workstation fails, the software method is used to switch the screen content and data transmission channel of the failed graphic workstation to the standby graphic workstation, so as to ensure that the failure can be automatically shielded in the shortest time and the large screen can quickly return to the normal display state. © 2023 IEEE.

关键词： Display devices

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Novel vision-LiDAR fusion framework for human action recognition based on dynamic lateral connection

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IET Cyber-systems and Robotics 2024年第4期6卷 21-31页

作者： Fei Yan Guangyao Jin Zheng Mu Shouxing Zhang Yinghao Cai Tao Lu Yan Zhuang The School of Control Science and Engineering Dalian University of TechnologyDalianChina Technology Centre of Dalian Customs Dalian CustomsDalianChina ZX‐YZ School of Network Science Haikou University of EconomicsHainanChina The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijingChina

In the past decades,substantial progress has been made in human action ***,most existing studies and datasets for human action recognition utilise still images or videos as the primary ***-based approaches can be easily impacted by adverse environmental *** this paper,the authors propose combining RGB images and point clouds from LiDAR sensors for human action recognition.A dynamic lateral convolutional network(DLCN)is proposed to fuse features from *** RGB features and the geometric information from the point clouds closely interact with each other in the DLCN,which is complementary in action *** experimental results on the JRDB-Act dataset demonstrate that the proposed DLCN outperforms the state-of-the-art approaches of human action *** authors show the potential of the proposed DLCN in various complex scenarios,which is highly valuable in real-world applications.

关键词： neural network-based pedestrian identification sensor fusion

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Convex Equilibrium-Free Stability and Performance Analysis of Discrete-Time Nonlinear systems

arXiv

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arXiv 2024年

作者： Koelewijn, Patrick J.W. Weiland, Siep Tóth, Roland Control Systems Group Department of Electrical Engineering Eindhoven University of Technology Netherlands Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Hungary

This paper considers the equilibrium-free stability and performance analysis of discrete-time nonlinear systems. We consider two types of equilibrium-free notions. Namely, the universal shifted concept, which considers stability and performance w.r.t. all equilibrium points of the system, and the incremental concept, which considers stability and performance between trajectories of the system. In this paper, we show how universal shifted stability and performance of discrete-time systems can be analyzed by making use of the time-difference dynamics. Moreover, we extend the existing results for incremental dissipativity for discrete-time systems based on dissipativity analysis of the differential dynamics to more general state-dependent storage functions for less conservative results. Finally, we show how both these equilibrium-free notions can be cast as a convex analysis problem by making use of the linear parameter-varying framework, which is also demonstrated by means of an example. Copyright © 2024, The Authors. All rights reserved.

关键词： Nonlinear systems

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Gaussian-Process-based Adaptive Tracking control with Dynamic Active Learning for Autonomous Ground Vehicles

arXiv

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arXiv 2025年

作者： Floch, Kristóf Péni, Tamás Tóth, Roland Systems and Control Laboratory HUN-REN Inst. for Computer Science and Control Budapest1111 Hungary Control Systems Group Eindhoven University of Technology Eindhoven6512 Netherlands

This article proposes an active-learning-based adaptive trajectory tracking control method for autonomous ground vehicles to compensate for modeling errors and unmodeled dynamics. The nominal vehicle model is decoupled into lateral and longitudinal subsystems, which are augmented with online Gaussian Processes (GPs), using measurement data. The estimated mean functions of the GPs are used to construct a feedback compensator, which, together with an LPV state feedback controller designed for the nominal system, gives the adaptive control structure. To assist exploration of the dynamics, the paper proposes a new, dynamic active learning method to collect the most informative samples to accelerate the training process. To analyze the performance of the overall learning tool-chain provided controller, a novel iterative, counterexample-based algorithm is proposed for calculating the induced L2 gain between the reference trajectory and the tracking error. The analysis can be executed for a set of possible realizations of the to-be-controlled system, giving robust performance certificate of the learning method under variation of the vehicle dynamics. The efficiency of the proposed control approach is shown on a high-fidelity physics simulator and in real experiments using a 1/10 scale F1TENTH electric car. © 2025, CC BY.

关键词： State feedback

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Fault localization for intelligent automation systems 28

Fault localization for intelligent automation systems

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28th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2023

作者： Eros, Endre Bengtsson, Kristofer Åkesson, Knut Chalmers University of Technology Automation Research Group Electrical Engineering Systems and Control Department Gothenburg Sweden Volvo Group As Senior Researcher for Smart and Connected Operations Research and Technology Development Gothenburg Sweden

ISBN: (纸本)9798350339918

Conventional programming of explicit control code is unsuitable for flexible and collaborative production systems. A model-based approach, which focuses on defining capabilities of a system, instead of specifying how to achieve them, provides an alternative for creating complex, scalable, and reliable systems. This is accomplished through the use of behavior models, and tools such as planning, synthesis, verification, and testing. However, developing such models is not without challenges, as it is possible to overlook or incorrectly specify potential behavior and constraints. This can result in unsolvable planning problems or plans that are invalid for other reasons. When plans are unobtainable, developers receive no feedback, which makes model adjustments a difficult and time-intensive task. This paper recognizes these challenges as crucial barriers for adopting model-based development of intelligent automation systems. To facilitate the development of such systems, an approach for detecting and localizing faults in behavior models is presented. Drawing inspiration from software fault localization techniques, the proposed method involves identifying suspicious resources, variables, and operations. The effectiveness of this approach is illustrated with an example use case. © 2023 IEEE.

关键词： Automation

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Gaussian-Process-Based Adaptive Trajectory Tracking control for Autonomous Ground Vehicles

Gaussian-Process-Based Adaptive Trajectory Tracking Control ...

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European control Conference (ECC)

作者： Kristóf Floch Tamás Péni Roland Tóth Systems and Control Lab HUN-REN Inst. for Computer Science and Control Budapest Hungary Control Systems Group Eindhoven University of Technology Eindhoven The Netherlands

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

This paper proposes an adaptive trajectory tracking control algorithm for autonomous ground vehicles. The nonlinear vehicle dynamics are decoupled into two subsystems corresponding to the longitudinal and lateral motions. Each subsystem is augmented with a Gaussian Process to compensate for modeling errors and external disturbances. Based on the augmented subsystems, adaptive control algorithms are synthesized. To give a mathematically correct performance measure, the induced $\mathcal{L}_2$ -gain of the nonlinear closed-loop system is computed. The efficiency of the learning-based control method is demonstrated on a high-fidelity physical simulator using a digital twin model of the 1/10 scale F1TENTH vehicle platform.

关键词： Adaptation models Uncertainty Trajectory tracking Heuristic algorithms Computational modeling Mathematical models Land vehicles

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An activated variable parameter gradient‐based neural network for time‐variant constrained quadratic programming and its applications

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CAAI Transactions on Intelligence technology 2023年第3期8卷 670-679页

作者： Guancheng Wang Zhihao Hao Haisheng Li Bob Zhang PAMI Research Group Department of Computer and Information ScienceUniversity of MacaoTaipaMacaoChina China Industrial Control Systems Cyber Emergency Response Team BeijingChina Beijing Key Laboratory of Big Data Technology for Food Safety Beijing Technology and Business UniversityBeijingChina

This study proposes a novel gradient‐based neural network model with an activated variable parameter,named as the activated variable parameter gradient‐based neural network(AVPGNN)model,to solve time‐varying constrained quadratic programming(TVCQP)*** with the existing models,the AVPGNN model has the following advantages:(1)avoids the matrix inverse,which can significantly reduce the computing complexity;(2)introduces the time‐derivative of the time‐varying param-eters in the TVCQP problem by adding an activated variable parameter,enabling the AVPGNN model to achieve a predictive calculation that achieves zero residual error in theory;(3)adopts the activation function to accelerate the convergence *** solve the TVCQP problem with the AVPGNN model,the TVCQP problem is transformed into a non‐linear equation with a non‐linear compensation problem function based on the Karush Kuhn Tucker ***,a variable parameter with an activation function is employed to design the AVPGNN *** accuracy and convergence rate of the AVPGNN model are rigorously analysed in ***,numerical experiments are also executed to demonstrate the effectiveness and superiority of the proposed ***,to explore the feasibility of the AVPGNN model,appli-cations to the motion planning of a robotic manipulator and the portfolio selection of marketed securities are illustrated.

关键词： computational intelligence mathematics computing optimisation

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Data-enabled Predictive Repetitive control

Data-enabled Predictive Repetitive Control

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IEEE Conference on Decision and control

作者： Rogier Dinkla Tom Oomen Sebastiaan P. Mulders Jan-Willem van Wingerden Delft Center for Systems and Control Mekelweg 2 Delft University of Technology Delft The Netherlands Control Systems Technology Group Eindhoven University of Technology Eindhoven The Netherlands

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Many systems are subject to periodic disturbances and exhibit repetitive behaviour. Model-based repetitive control employs knowledge of such periodicity to attenuate periodic disturbances and has seen a wide range of successful industrial implementations. The aim of this paper is to develop a data-driven repetitive control method. In the developed framework, linear periodically time-varying (LPTV) behaviour is lifted to linear time-invariant (LTI) behaviour. Periodic disturbance mitigation is enabled by developing an extension of Willems’ fundamental lemma for systems with exogenous disturbances. The resulting Data-enabled Predictive Repetitive control (DeePRC) technique accounts for periodic system behaviour to perform attenuation of a periodic disturbance. Simulations demonstrate the ability of DeePRC to effectively mitigate periodic disturbances in the presence of noise.

关键词： Linear systems Prevention and mitigation Noise Attenuation

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Space-Filling Input Design for Nonlinear State-Space Identification

arXiv

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arXiv 2024年

作者： Kiss, Máté Tóth, Roland Schoukens, Maarten Control System group Eindhoven University of Technology Eindhoven Netherlands Systems and Control Laboratory Institute for Computer Science and Control Budapest Hungary

The quality of a model resulting from (black-box) system identification is highly dependent on the quality of the data that is used during the identification procedure. Designing experiments for linear time-invariant systems is well understood and mainly focuses on the power spectrum of the input signal. Performing experiment design for nonlinear system identification on the other hand remains an open challenge as informativity of the data depends both on the frequency-domain content and on the time-domain evolution of the input signal. Furthermore, as nonlinear system identification is much more sensitive to modeling and extrapolation errors, having experiments that explore the considered operation range of interest is of high importance. Hence, this paper focuses on designing space-filling experiments i.e., experiments that cover the full operation range of interest, for nonlinear dynamical systems that can be represented in a state-space form using a broad set of input signals. The presented experiment design approach can straightforwardly be extended to a wider range of system classes (e.g., NARMAX). The effectiveness of the proposed approach is illustrated on the experiment design for a nonlinear mass-spring-damper system, using a multisine input signal. © 2024, CC BY-NC-SA.

关键词： Frequency domain analysis

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