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Koopman Representation for Boolean Networks

IFAC-PapersOnLine 2023年第2期56卷 6678-6683页

作者： Hongsheng Qi Maria Elena Valcher Guodong Shi Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing 100049 China Dipartimento di Ingegneria dell'Informazione Universita’ di Padova Padova 35131 Italy Australian Center for Robotics School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney NSW 2006 Australia

Boolean networks, as logical dynamical systems whose system states are Boolean variables, arise from applications in biology, computer networks, and social networks etc. The representation and control of Boolean networks have attracted a lot of attention in recent years. On a parallel line of research, Koopman developed an operator view of nonlinear dynamical systems in early 1930s, which shows that using observable functions all nonlinear dynamics can be represented as (infinite dimensional) linear systems. In this paper, we present a framework for representing Boolean networks via Koopman approach. First of all, we construct addition and scalar multiplication operations over the set of logical functions over the binary field, defining a linear Boolean function space. Then associated with any Boolean mapping, the induced Koopman operator is defined as an operator over such Boolean function space. Next, we show that if there exists a set of logical functions that are invariant in the Koopman sense, a Boolean network can be represented by a finite-dimensional linear system. This Koopman perspective for Boolean networks is also extended to controlled Boolean networks.

关键词： Boolean networks Koopman operator

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Improved Diagnosis of Lithium-Ion Battery Health in Electric Vehicles via a Hybrid Deep Learning Model Incorporating Wavelet Transform and Attention Mechanism

Improved Diagnosis of Lithium-Ion Battery Health in Electric...

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Artificial Intelligence & Green Energy (ICAIGE), IEEE International Conference on

作者： Walid Mchara Mohamed Abdellatif Khalfa Lazhar Manai Laboratory of Robotics Informatics and Complex Systems (RISC) National Engineering School of Tunis (ENIT) University of El Manar Le Belvedere Tunis Higher Institute of Information and Communication Technologies Hamam Chatt Tunisia LaNSER Laboratory CRETn Borj-Cedria RISC Le Belvédère Tunis Tunisia ENIT University of El Manar

ISBN: (数字)9798350389838

ISBN: (纸本)9798350389845

As the adoption of lithium-ion batteries (LIBs) in electric vehicles increases, ensuring their reliability and safety is essential. The Battery Management System (BMS) is vital for accurately evaluating the State of Health (SOH) of these batteries to ensure safe vehicle operation. To address this, a novel time series model for predicting SOH in Li-ion batteries is proposed. This model combines wavelet transform with a hybrid architecture of convolutional neural networks (CNNs) and long short-term memory (LSTM) networks, enhanced by an attention mechanism to improve performance. Experimental results indicate that the wavelet-enhanced LSTM method significantly improves prediction accuracy. This study presents a promising approach to enhance the reliability and efficiency of electric vehicle battery systems, supporting broader adoption and sustainability in electric transportation.

关键词： Wavelet transforms Lithium-ion batteries Deep learning Attention mechanisms Accuracy Predictive models Prediction algorithms Convolutional neural networks Reliability Long short term memory

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Vibrational Stabilization of Cluster Synchronization in Oscillator Networks

arXiv

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arXiv 2023年

作者： Qin, Yuzhen Nobili, Alberto Maria Bassett, Danielle S. Pasqualetti, Fabio Department of Mechanical Engineering University of California RiversideCA United States Perceptual Robotics Laboratory at the IIM Institute Department of Excellence in Robotics and A.I. Scuola Superiore Sant’Anna Pisa Italy Department of Bioengineering Department of Electrical & Systems Engineering Department of Physics & Astronomy The Department of Psychiatry Department of Neurology University of Pennsylvania The Santa Fe Institute United States

Cluster synchronization is of paramount importance for the normal functioning of numerous technological and natural systems. Deviations from normal cluster synchronization patterns are closely associated with various malfunctions, such as neurological disorders in the brain. Therefore, it is crucial to restore normal system functions by stabilizing the appropriate cluster synchronization patterns. Most existing studies focus on designing controllers based on state measurements to achieve system stabilization. However, in many real-world scenarios, measuring system states, such as neuronal activity in the brain, poses significant challenges, rendering the stabilization of such systems difficult. To overcome this challenge, in this paper, we employ an open-loop control strategy, vibrational control, which does not requires any state measurements. We establish some sufficient conditions under which vibrational inputs stabilize cluster synchronization. Further, we provide a tractable approach to design vibrational control. Finally, numerical experiments are conducted to demonstrate our theoretical findings. Copyright © 2023, The Authors. All rights reserved.

关键词： Brain

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Design and analysis of a soft bellow-based robot for dysphagia rehabilitation 30

Design and analysis of a soft bellow-based robot for dysphag...

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30th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2024

作者： Guo, Linlin Dang, Yu Wang, Yue Wu, Jinqiao Yu, Yang Wu, Jialing Han, Jianda College of Artificial Intelligence Nankai University Tianjin300350 China Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Nankai University Tianjin300350 China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin300350 China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute Nankai University Shenzhen518083 China Department of Rehabilitation Medicine Tianjin Huanhu Hospital Tianjin300350 China Department of Neurology Tianjin Huanhu Hospital Tianjin300350 China

ISBN: (纸本)9798350391916

As the population ages, the incidence of diseases such as stroke is increasing, leading to a growing number of patients with dysphagia or difficulty swallowing. Dysphagia directly affects the hydration and nutritional intake, potentially leading to serious complications such as aspiration pneumonia, severely threatening patients' health and quality of life. Currently, the rehabilitation of swallowing function mainly relies on therapists to conduct swallowing training for patients. However, the high incidence and long duration of swallowing rehabilitation training pose a burden on the patients and medical resources. There remains a gap in the robotic devices for swallowing rehabilitation. To address this gap, this paper proposes a soft bellow-shaped robot for dysphagia rehabilitation. One mode of the rehabilitation training, where the therapist manipulates the throat to move horizontally, is selected to mimic. This robot simulates the force and displacement applied by the therapist's fingertip during dysphagia rehabilitation. First, swallowing training data were collected and analyzed to understand the variations in displacement and force applied by therapists' fingertips on the throat. Based on this analysis, the technical requirements for the swallowing rehabilitation robot were summarized. Following these requirements, we designed a physical prototype of the pneumatic bellow-shaped robot. The robot simulates the fingertip movement on both sides of the throat through the linear elongation and contraction of the bellows. The performance of the soft bellows was then characterized, verifying that its output force and displacement meet the technical requirements. This characterization lays a foundation for the modeling and control of the displacement and force of the robot. © 2024 IEEE.

关键词： Bellows

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A modified YOLOv4 detection method for a vision-based underwater garbage cleaning robot

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Frontiers of Information Technology & Electronic engineering 2022年第8期23卷 1217-1228页

作者： Manjun TIAN Xiali LI Shihan KONG Licheng WU Junzhi YU First Research Institute of the Ministry of Public Security of PRC Beijing 100048China School of Information Engineering Minzu University of ChinaBeijing 100081China Department of Advanced Manufacturing and Robotics College of EngineeringPeking UniversityBeijing 100871China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

To tackle the problem of aquatic environment pollution,a vision-based autonomous underwater garbage cleaning robot has been developed in our *** propose a garbage detection method based on a modified YOLOv4,allowing high-speed and high-precision object ***,the YOLOv4 algorithm is chosen as a basic neural network framework to perform object *** the purpose of further improvement on the detection accuracy,YOLOv4 is transformed into a four-scale detection *** improve the detection speed,model pruning is applied to the new *** virtue of the improved detection methods,the robot can collect garbage *** detection speed is up to 66.67 frames/s with a mean average precision(mAP)of 95.099%,and experimental results demonstrate that both the detection speed and the accuracy of the improved YOLOv4 are excellent.

关键词： Object detection Aquatic environment Garbage cleaning robot Modified YOLOv4

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A Piecewise Monotonic Gait Phase Estimation Model for Controlling a Powered Transfemoral Prosthesis in Various Locomotion Modes

arXiv

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arXiv 2022年

作者： Chen, Xinxing Chen, Chuheng Wang, Yuxuan Yang, Bowen Ma, Teng Leng, Yuquan Fu, Chenglong Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Shenzhen518055 China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen518055 China Department of Biomedical Engineering National University of Singapore Singapore

Gait phase-based control is a trending research topic for walking-aid robots, especially robotic lower-limb prostheses. Gait phase estimation is a challenge for gait phase-based control. Previous researches used the integration or the differential of the human's thigh angle to estimate the gait phase, but accumulative measurement errors and noises can affect the estimation results. In this paper, a more robust gait phase estimation method is proposed using a unified form of piecewise monotonic gait phase-thigh angle models for various locomotion modes. The gait phase is estimated from only the thigh angle, which is a stable variable and avoids phase drifting. A Kalman filter-based smoother is designed to further suppress the mutations of the estimated gait phase. Based on the proposed gait phase estimation method, a gait phase-based joint angle tracking controller is designed for a transfemoral prosthesis. The proposed gait estimation method, the gait phase smoother, and the controller are evaluated through offline analysis on walking data in various locomotion modes. And the real-time performance of the gait phase-based controller is validated in an experiment on the transfemoral prosthesis. © 2022, CC BY.

关键词： Controllers

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Trajectory Tracking Error Optimization based on Iterative Learning 4

Trajectory Tracking Error Optimization based on Iterative Le...

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4th IEEE International Conference on Power, Intelligent Computing and systems, ICPICS 2022

作者： Huang, Haoran Zhang, Tao Jia, Danping Zhang, Hualiang Yan, Hongyu Pei, Quanshen Ding, Fan Shenyang University of Technology School of Information Science and Engineering Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China School of Artificial Intelligence Shenyang University of Technology Shenyang China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

The X-Y precision plane motion platform is widely used in various precision motion control fields. In this paper, to improve the tracking accuracy of the X-Y precision plane motion table, a high-level iterative learning control with forgetting factor is proposed, and it is combined with a kind of PD-type iterative learning control with low-pass filter, and the method is applied to the Simulink model of the linear motor of the X-Y precision plane platform, thereby improving the trajectory accuracy of the X-Y precision plane motion platform. The traditional ILC has the disadvantage that the more number of iterations, the more divergent tracking error is. The new ILC proposed in this paper can not only effectively reduce the noise, reduce the tracking error, but also eliminate the problem of error divergence caused by too many iterations. At last, the experimental results of high-order PD iterative learning with forgetting factor and low-pass filter, PD iterative learning with low-pass filter, ordinary PD iterative learning are compared. The results show that the high-order PD iterative learning with forgetting factor and low-pass filter has better tracking effect than the first-order iterative learning and other several algorithms. It can make the movement trajectory of the X-Y precision plane motion platform more stable and improve the accuracy. © 2022 IEEE.

关键词： Low pass filters

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A Novel Signals and Features Fusion Method Based on Fisher Vector for Severity Assessment in Parkinson's Disease 8

A Novel Signals and Features Fusion Method Based on Fisher V...

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8th IEEE International Conference on Advanced robotics and Mechatronics, ICARM 2023

作者： Sun, Yubo Cheng, Yuanyuan Zhu, Zhizhong Liu, Jinrui Guo, Zhenhui Yu, Ningbo College of Artificial Intelligence Nankai University Tianjin300350 China Tianjin Huanhu Hospital Department of Rehabilitation Medicine Tianjin300350 China Nankai University Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Tianjin300350 China Nankai University Tianjin Key Laboratory of Intelligent Robotics Tianjin300350 China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen518083 China

ISBN: (纸本)9798350300178

Parkinson's disease (PD) is a progressive neurode-generative disorder that requires accurate severity assessment to facilitate proper medication and interventions. This study proposes a novel method for PD severity assessment by fusing bilateral surface electromyography (sEMG) signals and features using Fisher vector. The sEMG signals were measured from the tibialis anterior (TA) and lateral gastrocnemius (GL) muscles in 28 PD patients. Preprocessing was performed to remove industrial frequency noise and low-frequency trend, followed by feature extraction using a customized feature generator that included time-domain and frequency-domain features. The extracted features and preprocessed sEMG signals were then vectorized using the Fisher vector and fused as input to the classifier. Our results demonstrated that considering bilateral features is more favorable than unilateral features for the PD severity assessment. Moreover, the proposed method significantly enhanced the classification accuracy, with a remarkable classification accuracy of 96.00% achieved through the combination of our proposed method with a decision tree classifier. © 2023 IEEE.

关键词： Time domain analysis

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Fast Realization of Robot 3D Simulation Based on WebGL

Fast Realization of Robot 3D Simulation Based on WebGL

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第35届中国控制与决策会议

作者： Tao Zhang Xintong Wang Yun Teng Jingzhe Fang Yiqiang Zhang Xiyou Chen School of Electrical Engineering Dalian University of Technology Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences School of Electrical Engineering Shenyang University of Technology

As science and technology have advanced,an increasing number of people are focusing their study on 3 D robot *** 3 D quick simulation of the mechanical arm can be achieved using 3 D modeling software and *** the third-party WebGL library *** to construct the simulation scenario,then interact with and render the 3 D scene and 3 D robot model directly on the Web,which is easier and faster than downloading *** essay briefly explains the benefits and applicability of *** in the creation of 3 D virtual simulations,then goes on to discuss the quick implementation process of 3 D robot simulations before summarizing the building technique.

关键词： webgl three.js 3D simulation robot

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Trajectory Planning Towards Water-Air Trans-Media Motion for Robotic Dolphin

Trajectory Planning Towards Water-Air Trans-Media Motion for...

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Chinese Automation Congress (CAC)

作者： Yan Xiong Pengfei Zhang Di Chen Junzhi Yu Department of Advanced Manufacturing and Robotics State Key Laboratory for Turbulence and Complex Systems College of Engineering Peking University Beijing China Shandong Nuclear Power Company LTD. Yantai China School of Intelligence Science and Technology University of Science and Technology Beijing Beijing China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Water-air trans-media navigators have multi-media motion modes, breaking through the limitation that traditional robots can only operate in a single medium. Autonomous navigation is an indispensable component of the process of transmedia motion. Most of the current work has only completed the development and testing of prototypes, and the problem of task-oriented motion planning and control needs to be solved. In this paper, a safe and efficient hierarchical approach is proposed. First, a novel rapidly exploring random tree-based algorithm is proposed to search for a suitable path. Then, by fixing bound waypoints, the time-optimization trajectory is planned. Finally, the trajectory tracker is designed based on nonlinear model predictive control (NMPC). Simulation experiments numerically validate the proposed method, offering some new insights for further trans-media motions.

关键词： Tracking Trajectory planning Navigation Prototypes Prediction algorithms Trajectory Planning Testing Predictive control Dolphins

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