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Parametric Transformation of Timed Weighted Marked Graphs:Applications in Optimal Resource Allocation

IEEE/CAA Journal of Automatica Sinica 2021年第1期8卷 179-188页

作者： Zhou He Ziyue Ma Zhiwu Li Alessandro Giua the College of Mechanical and Electrical Engineering Shaanxi University of Science and TechnologyXi’an 710021China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of TechnologyXi’an 710048China the School of Electro-Mechanical Engineering Xidian UniversityXi’an 710071China Institute of Systems Engineering Macao University of Science and TechnologyTaipa 999078MacaoChina the Department of Electrical and Electronic Engineering University of CagliariCagliari 09124Italy

Timed weighted marked graphs are a subclass of timed Petri nets that have wide applications in the control and performance analysis of flexible manufacturing *** to the existence of multiplicities(i.e.,weights)on edges,the performance analysis and resource optimization of such graphs represent a challenging *** this paper,we develop an approach to transform a timed weighted marked graph whose initial marking is not given,into an equivalent parametric timed marked graph where the edges have unitary *** order to explore an optimal resource allocation policy for a system,an analytical method is developed for the resource optimization of timed weighted marked graphs by studying an equivalent ***,we apply the proposed method to a flexible manufacturing system and compare the results with a previous heuristic *** analysis shows that the developed approach is superior to the heuristic approach.

关键词： Discrete event system resource allocation timed Petri net weighted marked graph

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Disturbance Rejection for Pedaling Rehabilitation Robot Based on Integration of Equivalent-Input-Disturbance and Repetitive control Methods 32

Disturbance Rejection for Pedaling Rehabilitation Robot Base...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Zhou, Yujian She, Jinhua Wang, Feng Iwasaki, Makoto School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Tokyo University of Technology School of Engineering Tokyo Hachioji192-0982 Japan Nagoya Institute of Technology Department of Electrical and Mechanical Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350399714

This study integrated an improved equivalent-input-disturbance (EID) and a repetitive control methods to ensure reference tracking and enhance disturbance-rejection performance for a pedaling rehabilitation robot. A repetitive controller ensures steady-state tracking of a periodic reference input. An EID estimator with a state observer estimates and compensates for the effect of disturbances generated by patients with lower-limb impairment. The stability condition of the closed-loop system is analyzed based on the Lyapunov stability theory. Simulation results show the effectiveness of this method. © 2023 IEEE.

关键词： Disturbance rejection

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Adaptive Distributed Cluster Flow control for a Group of Autonomous Robots*

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IFAC-PapersOnLine 2023年第2期56卷 8690-8695页

作者： V. Erofeeva V. Ershov O. Granichin V. Pankov D. Uzhva O. Granichina Laboratory “Control of Complex Systems” Institute for Problems in Mechanical Engineering V.O. Bolshoy 61 199178 Saint Petersburg Faculty of Mathematics and Mechanics Research Laboratory for Analysis and Modeling of Social Processes Saint Petersburg State University 7/9 Universitetskaya Emb. 199034 Saint Petersburg Institute of Childhood Herzen State Pedagogical University 48 Moika Embankment 191186 Saint Petersburg

Conventional multiagent control strategies rely either on pre-defined operational patterns, or complex inter-agent communications. While the former provides simple yet compelling results, the latter allows to achieve goals in complex environments with unpredictable disturbances. However, designing local networked control solutions for large-scale robotic systems is extremely challenging. A novel way to control complex systems by manipulating system clusters as sub-systems is proposed. The relation between sparsity and cluster flows is manifested in the new developed approach to estimate cluster structure of a group of robots based only on a few local observations of their states. Aiming to perform necessary measurements of all N agent states, the compressed sensing methodology is used to obtain ∼ logN randomized aggregated measurements, followed by the corresponding series of local voting protocols for the network to reach a common aggregated state with randomized weights. Thus, the cluster control synthesis by these compressed measurements is computationally efficient, and yet precise. Effectiveness of the proposed method is illustrated in numeric simulations, where adaptive observation feedback cluster control outperforms conventional strategies.

关键词： Adaptive control of multi-agent systems Networked robotic systems Distributed optimization for large-scale systems

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Thickness evolution of commercial Li-ion pouch cells with siliconbased composite anodes and NCA cathodes

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Science China(Technological Sciences) 2021年第1期64卷 83-90页

作者： ZHANG XingYu HE Jie ZHOU Jiang CHEN HaoSen SONG WeiLi FANG DaiNing State Key Laboratory of Mechanics and Control of Mechanical Structures College of Aerospace EngineeringNanjing University of Aeronautics and AstronauticsNanjing 210016China State Key Laboratory of Explosion Science and Technology Institute of Advanced Structure TechnologyBeijing Institute of TechnologyBeijing 100081China Lishen Research Institute Tianjin Lishen Battery Joint-stock Co.Ltd.Tianjin 300384China State Key Laboratory for Turbulence and Complex Systems College of EngineeringPeking UniversityBeijing 100871China

It is significant to monitor the thickness change of commercial Li-ion pouch cells that are assembled from Si-based electrodes and layered cathodes since the volume variation is critically linked with kinetic reaction mechanism and chemomechanical degradation. In this work, the single-point and full-field measurements are conducted on the thickness evolution of Si Ox/Cgraphite/lithium nickel-cobalt-aluminum oxide(Si Ox-G/NCA) batteries. It is found that an abnormal overshoot that has been rarely observed in the previous studies appears at the beginning of discharge, which is believed to be the combined results between the rapid expansion of NCA and the contraction of graphite related to the state of charge(SOC). Compared with the results of single-point measurement, the spatial displacement distribution obtained from three-dimensional(3D) scanning suggests the full-field thickness evolution of the entire cell scale, which is more feasible and efficient to provide full-field information for supporting pouch cell design and pack integration.

关键词： thickness change 3D scanning silicon-based anode NCA cathode lithium-ion battery

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

AdvDiffuser: Generating Adversarial Safety-Critical Driving ...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

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

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

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.

关键词： Training Diffusion models Intelligent robots Autonomous vehicles Testing

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Photovoltaic Arrays’ Dynamic Model Parameter Estimation

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IFAC-PapersOnLine 2023年第2期56卷 6845-6850页

作者： Alexey Bobtsov Fernando Mancilla-David Stanislav Aranovskiy Romeo Ortega Faculty of Control Systems and Robotics ITMO University 197101 Saint Petersburg Russia Laboratory “Control of Complex Systems” Institute of Problems of Mechanical Engineering V.O. Bolshoj pr. 61 St. Petersburg 199178 Russia University of Colorado Denver Denver Colorado 80204 USA IETR – CentaleSupélec Cesson-Sévigné France Departamento Académico de Sistemas Digitales ITAM México

This paper deals with the problem of on-line identification of the parameters of a realistic dynamical model of a photovoltaic array connected to a power system through a power converter. It has been shown in the literature that, when interacting with switching devices, this model is able to better account for the PV array operation, as compared to the classical five parameter static model of the array. While there are many results of identification of the parameters of the latter model, to the best of our knowledge, no one has provided a solution for the aforementioned more complex dynamic model since it concerns the parameter estimation of a nonlinear, underexcited system with unmeasurable state variables. Achieving such objective is the main contribution of the paper. We propose a new parameterisation of the dynamic model, which, combined with the powerful identification technique of dynamic regressor extension and mixing, ensures a fast and accurate online estimation of the unknown parameters. Realistic numerical examples via computer simulations are presented to assess the performance of the proposed approach—even being able to track the parameter variations when the system changes operating point.

关键词： photovoltaic arrays on-line parameter estimation identification of nonlinear systems

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Compressed Cluster Sensing in Multiagent IoT control

Compressed Cluster Sensing in Multiagent IoT Control

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IEEE Conference on Decision and control

作者： Denis Uzhva Oleg Granichin Olga Granichina Laboratory "Control of Complex Systems" Institute for Problems in Mechanical Engineering Saint Petersburg Department of Software Engineering Mathematics and Mechanics Saint Petersburg State University Saint Petersburg Herzen State Pedagogical University Saint Petersburg

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

Traditional multiagent system control relies primarily on inter-agent local communications. In large-scale IoT systems it may appear hard to synthesize local control actions in a simple manner. Cluster control possibilities are thus thoroughly discussed, with possible control goals stated. The relation between multiagent state sparsity and cluster patterns is illustrated, for further utilization of sparsity for cluster control. Consequently, the problem of cluster identification is stated, and a possible solution is proposed in the form of the compressed cluster sensing algorithm. The algorithm utilizes compressed sensing methodology for a compact representation of agent states, which is then used to synthesize compact control actions in a low-dimensional space, without requiring to specify cluster locations.

关键词： Wireless sensor networks Heuristic algorithms Clustering algorithms Sensors Numerical models Nonlinear dynamical systems Synchronization

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Pilot-Induced Oscillations Prevention During Aircraft Flight in Formation 5

Pilot-Induced Oscillations Prevention During Aircraft Flight...

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5th Scientific School on Dynamics of complex Networks and their Applications, DCNA 2021

作者： Zaitceva, Iuliia Andrievsky, Boris Control of Complex Systems Lab Institute for Problems in Mechanical Engineering of the RAS Department of Applied Cybernetics St. Petersburg State University Saint Petersburg Russia Lappeenranta-Lahti University of Technology LUT Lappeenranta Finland

ISBN: (纸本)9781665442824

The paper is devoted to preventing oscillations in the angular motion of piloted aircraft by the pseudo-linear correcting device. The prime cause of this event is the unfavorable interaction between the pilot and the vehicle or the so-called pilot-induced oscillations. In this connection, it becomes necessary to consider the human influence on the piloting process to preserve the formation. © 2021 IEEE

关键词： Aircraft

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Open-/Closed-loop Active Learning for Data-driven Predictive control

arXiv

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arXiv 2024年

作者： Feng, Shilun Shi, Dawei Shi, Yang Zheng, Kaikai The State Key Laboratory of Intelligent Control and Decision of Complex Systems MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing Institute of Technology Beijing100081 China The Department of Mechanical Engineering Faculty of Engineering University of Victoria VictoriaBCV8N 3P6 Canada

An important question in data-driven control is how to obtain an informative dataset. In this work, we consider the problem of effective data acquisition of an unknown linear system with bounded disturbance for both open-loop and closed-loop stages. The learning objective is to minimize the volume of the set of admissible systems. First, a performance measure based on historical data and the input sequence is introduced to characterize the upper bound of the volume of the set of admissible systems. On the basis of this performance measure, an open-loop active learning strategy is proposed to minimize the volume by actively designing inputs during the open-loop stage. For the closed-loop stage, an closed-loop active learning strategy is designed to select and learn from informative closed-loop data. The efficiency of the proposed closed-loop active learning strategy is proved by showing that the unselected data cannot benefit the learning performance. Furthermore, an adaptive predictive controller is designed in accordance with the proposed data acquisition approach. The recursive feasibility and the stability of the controller are proved by analyzing the effect of the closed-loop active learning strategy. Finally, numerical examples and comparisons illustrate the effectiveness of the proposed data acquisition strategy. Copyright © 2024, The Authors. All rights reserved.

关键词： Active learning

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Differential Steering control for 6 × 6 Wheel-drive Mobile Robot 26

Differential Steering Control for 6 × 6 Wheel-drive Mobile ...

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26th International Conference on Automation and Computing, ICAC 2021

作者： Zhao, Hongqiang Luo, Chao Xu, Yongkang Li, Jiehao Central South University State Key Laboratory of High Performance Complex Manufacturing School of Mechanical and Electrical Engineering ChangSha China Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing China

ISBN: (纸本)9781860435577

The 6 × 6 Wheel-drive mobile robot is widely used in the field of special operations, and there is the phenomenon of slipping in the process of steering. To study the steering accuracy and stability of mobile robot, the dynamic model of 6 × 6 Wheel-drive Mobile Robot is established, and the sliding mode control strategy of differential steering based on mobile robot is proposed. Firstly, taking the torque of six wheels and the operator's direction control as input, the three-dimensional attitude and the relative position of the steering center of the mobile robot are obtained by using the position and attitude sensor, to determine the reference steering angle of the mobile robot. Secondly, considering the relationship between the position error and the velocity error, a recursive sliding surface is designed, and a neural network is introduced to approach the uncertain part of the mobile robot model. Then, a nonlinear gain function is applied to construct a dynamic surface control law. Finally, through the Trucksim/Simulink co-simulation model, the nonlinear gain recursive sliding mode dynamic surface adaptive control method for mobile robot trajectory tracking can improve the tracking speed and control precision, and the control force and torque are smooth and reasonable. The results show that the method is effective in improving the steering accuracy and stability of mobile robot. © 2021 Chinese Automation and Computing Society in the UK-CACSUK.

关键词： Mobile robots

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