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2nd Asia Conference on Electronics Engineering, ACEE 2024

作者： Yuan, Ruijian Zhang, Yongli Geng, Lihui Li, Xuehui Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control School of Automation and Electrical Engineering Tianjin China

ISBN: (纸本)9798350375251

The two-wheeled bicycle robot (TWBR) is a new intelligent transportation, which can be used for special tasks such as forest operation and disaster relief. Although the TWBR is not structurally complex, the dynamics are very complex to model. It is extremely difficult to build an accurate mathematical model. Wind disturbance is, in principle, always present on open roads and influence on the driving stability increases. Aiming at mathematical modeling error caused by mass center of the TWBR frame and external disturbance caused by wind force, this paper introduces a suitable control method. Firstly, the Kane method is adopted for modeling. Secondly, robust control can provide stability and performance guarantee for both uncertainty and disturbance. Finally, the results of simulation and physical experiment show the effectiveness of the robust H∞ control for TWBR. In this paper, MATLAB/Simulink is used to establish a combined mathematical model of wind force as an experimental external disturbance. The robust H∞ controller based on linear matrix inequality (LMI) and Linear quadratic regulator(LQR) are realized. It is verified that the robust H∞ controller has better effectiveness than the LQR controller when facing the uncertainty and external disturbance. © 2024 IEEE.

关键词： Bicycles

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Optimal Scheduling of Provincial local Coordinated Based on Source-grid-load-storage Interactions 25

Optimal Scheduling of Provincial local Coordinated Based on ...

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25th IEEE China Conference on System Simulation technology and its Application, CCSSTA 2024

作者： Zhang, Haixuan Kong, Xiangyu Zhang, Delong Liu, Jiancun Zhou, Xuesong Liu, Mao Tianjin University of Technology Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin China Tianjin University Key Laboratory of Smart Grid Tianjin China

ISBN: (纸本)9798350366600

Considering the characteristics of coordination among source-network-load-storage, a provincial local coordinated scheduling method based on the interaction of sourcenetwork-load-storage is proposed. Firstly, the interaction mechanism of source-grid-load-storage is refined. Secondly, according to the spatial characteristics of the scheduling of provincial local coordinated, a multi-objective optimal scheduling model is established with the objectives of economy and new energy consumption. Thirdly, a genetic algorithm is used to solve the problem. Finally, by analyzing the examples, it is proved that the proposed method can reduce the system cost and improve the utilization rate of new energy. © 2024 IEEE.

关键词： Scheduling algorithms

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Parameter Identification and control of Two-Wheel Balance Vehicle Model Based on Subspace Algorithm 2

Parameter Identification and Control of Two-Wheel Balance Ve...

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2nd Asia Conference on Electronics Engineering, ACEE 2024

作者： Li, Xuehui Zhang, Yongli Geng, Lihui Yuan, Ruijian Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control School of Automation and Electrical Engineering Tianjin China

ISBN: (纸本)9798350375251

To address parameter uncertainty in the two-wheel balance vehicle (TWBV) system, a closed-loop subspace algorithm (CLSA) was employed to identify and correct uncertain structural parameters. This got in a more accurate system model. Based on the dynamics mechanism model of the TWBV, we designed a simple controller to achieve self-balancing control. We harvested the input and output sample data required for identification. The method used to filter out noise from the original signal and extract essential dynamic characteristics of the system is the input-output bias voltage function. The parameters of the dynamics model for the TWBV were subsequently identified and corrected using the CLSA. Finally, the linear quadratic regulator (LQR) controller is designed based on the model obtained from identification and compared with the original unidentified model. The results of the simulation and physical experiment show that the control system with the modified system after identification has better performance. This paper verifies the effectiveness of the proposed control strategy, which provides a reference scheme for solving model uncertainty in similar systems and improving control accuracy. © 2024 IEEE.

关键词： Vehicle wheels

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Mathematical Model of Adaptive Optimal Allocation for the Whole Process of Driving Through No. 18 Non-crossing Crossover Considering Special Sections 1

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6th International Conference on Electrical Engineering and Information Technologies for Rail Transportation, EITRT 2023

作者： Zhao, Ganghui Wang, Ying Chen, Xiaoqiang Wang, Yixuan Lanzhou Jiaotong University Lanzhou730070 China Key Laboratory of Opto-Technology and Intelligent Control Ministry of Education Lanzhou730070 China

ISBN: (数字)9789819993192

ISBN: (纸本)9789819993185

With the large-scale construction and the requirement of speed increase of high-speed railway in China, non-crossing crossover has been widely used in high-speed railway catenary. In order to satisfy the requirements of smooth operation of the line, a model of No. 18 non-crossing crossover based on the whole running process is proposed. Based on the whole process of driving through No. 18 non-crossing crossover, the operating principle of No. 18 non-crossing crossover is introduced, the whole model of No. 18 non-crossing crossover composed of line center and contact line model is established, the process of driving through two special sections of No. 18 non-crossing crossover initial contact area and contour area is studied, the influence of special section on the model of no-crossing crossover is considered, and the special section model of No. 18 non-crossing crossover is established. Based on the laboratory platform, the software of No. 18 non-crossing crossover is developed, and the model is validated by using the measured data of high-speed field of Ningdong Station from Yinchuan to Zhongwei of Yinlan Passenger Dedicated. The calcu-lation results show that the proposed model has the characteristics of validity, accuracy and real-time, and is suitable to the calculation of No. 18 non-crossing crossover in various situations. © 2024, Beijing Paike Culture Commu. Co., Ltd.

关键词： Railroads

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Review of Research on Motor Imagery in the Field of Rehabilitation 4

Review of Research on Motor Imagery in the Field of Rehabili...

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4th International Conference on Computer Science, Electronic Information Engineering and intelligent control technology, CEI 2024

作者： Ji, Xin Guo, Tinghang Li, Xiaohan Yin, Qianhan Li, Runze Qin, Zhuanping Han, Yu Lu, Guangda Control Automation and Electrical Engineering College Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing & Intelligent Tianjin China

ISBN: (纸本)9798350378542

Motor imagery has the advantages of non-invasiveness, safety and economic efficiency in post-stroke motor function rehabilitation, and has a wide application prospect in the field of medical rehabilitation. In this paper, we sort out the current status of the application of motor imagery brain-computer interface technology, summarize the development of motor imagery decoding algorithms and their application in the field of motor rehabilitation, discuss and analyze the research progress of motor imagery brain-computer interface technology in medical rehabilitation, and summarize the development trend of its development, so as to provide new therapeutic methods and ideas for the future of medical rehabilitation. © 2024 IEEE.

关键词： Medical imaging

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Optimized Complex Convolutional Neural Network for Steady-State Visual Evoked Potentials Signal classification 25

Optimized Complex Convolutional Neural Network for Steady-St...

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25th IEEE China Conference on System Simulation technology and its Application, CCSSTA 2024

作者： Li, Qingbin Han, Chunxiao Liu, Yanli Liu, Junxiu Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing & Intelligent Control School of Automation and Electrical Engineering Tianjin China

ISBN: (纸本)9798350366600

The steady-state visual evoked potential (SSVEP) is one of the most commonly used paradigms in the BCI system, which produces a significant response to visual stimuli of a specific frequency. How to better improve the classification performance of SSVEP signals is currently the main task. In this paper, a modified C-CNN-SVM model of EEG signal is proposed, aiming to enhance the precision of SSVEP signal classification. Firstly, spectral features are obtained from the SSVEP signal using fast fourier transform (FFT) as input to the model. FFT obtains 128 data lengths of the SSVEP signal, including 64 real part data and 64 complex part data. Then, CNN is used to further extract features, and finally, support vector machine (SVM) is used for classification. The experimental results show that the modified C-CNN-SVM model achieves an average accuracy of 93.86%, which is better than the traditional CCA, FBCCA and TRCA algorithms. © 2024 IEEE.

关键词： Convolutional neural networks

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Safety-Certified Distributed Formation control of Networked Autonomous Surface Vehicles by Unifying control Lyapunov and control Barrier Functions

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Journal of Systems Science & Complexity 2025年第2期38卷 837-856页

作者： CONG Siming GU Nan WANG Haoliang WANG Dan PENG Zhouhua School of Marine Electrical Engineering Dalian Maritime University State Key Laboratory of Maritime Technology and Safety Dalian Maritime University Dalian Key Laboratory of Swarm Control and Electrical Technology for Intelligent Ships School of Marine Engineering Dalian Maritime University Department of Automation Shanghai Jiaotong University Dalian KeyLaboratory of Swarm Control and Electrical Technology for Intelligent Ships

This paper investigates the path-guided distributed formation control of networked autonomous surface vehicles(ASVs) subject to model uncertainties and environmental disturbances. A safety-certified path-guided coordinated control method is proposed for multiple ASVs to achieve a distributed formation in obstacle environments. Specifically, a neural predictor with a high-order tuner is presented to approximate unknown nonlinearities with accelerated learning performance. Subsequently, control Lyapunov functions(CLFs) and control barrier functions(CBFs) are constructed for mapping stability constraints and safety constraints on states to control inputs. A quadratic optimization problem is constructed with the norm of control inputs as the objective function, CLFs and CBFs as constraints. Neurodynamic optimization is used to deal with the quadratic programming problem and generate the optimal kinetic control signals, thereby attaining the desired safe formation. Unlike the high-order CBF, a CBF backstepping method is proposed to establish safety constraints such that repeated time derivatives of system nonlinearities can be avoided. The multi-ASVs system is ensured to be input-to-state safe irrespective of high-order relative degree. Through the Lyapunov theory, the multi-ASVs system is proven to be input-to-state stable. Finally, simulation results are presented to validate the efficacy of the presented safety-certified distributed formation control for networked ASVs.

关键词： Autonomous surface vehicles control barrier functions neurodynamic optimization path-guided formation control safety-certified control

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Design of a Multi-motor control System for a Parallel Mechanism 4th

Design of a Multi-motor Control System for a Parallel Mechan...

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4th International Conference on Energy Power and Automation Engineering, ICEPAE 2023

作者： Wang, Yanchao Zhang, Hongxin Tian, Liguo Xie, Zikang Sun, Miao Tianjin University of Technology and Education Tianjin300222 China Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin300222 China

ISBN: (纸本)9789819988778

In this paper, a motion control system has been designed. The system is used to control twelve motors which drive a parallel mechanism by adjusting pulse width modulation (PWM) with a microcontroller. The motors are selected according to the characteristics of the parallel mechanism. And the dynamic model of the motor is established. Many related control experiments are done, and the control error is analyzed. It is shown that the motion control system designed in this paper can achieve more accurate control of the parallel mechanism experimentally. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Pulse width modulation

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Learning-Based Predictive control of Switched Nonlinear Systems via Koopman Modeling Approach

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Journal of Systems Science & Complexity 2025年第2期38卷 691-716页

作者： NING Zepeng FANG Xu LI Yibei XIE Lihua School of Electrical and Electronic Engineering Nanyang Technological University Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences

This paper proposes a data-driven learning-based approach to predictive control for switched nonlinear systems subject to state and control constraints and external stochastic disturbances. A switched Koopman modeling framework is developed, where a multi-mode neural network for state lifting is trained simultaneously with Koopman operators and state reconstruction matrices for all *** framework facilitates the construction of the switched linear Koopman model in a transformed space and effectively captures the dynamics of the original nonlinear system. A switched predictive control strategy is then designed to regulate the switched Koopman model with constrained states and control inputs against both the stochastic disturbances and the uncertainties introduced by the lifting neural network. The proposed control scheme ensures mean-square stability and guarantees boundedness during the online phase. Furthermore, boundedness analysis is performed to determine the bounded set of the original system state across all admissible switching sequences. The effectiveness of the proposed methodology is demonstrated through a case study of a gene regulatory network.

关键词： Data-driven machine learning model predictive control stochastic systems switched Koopman model switched nonlinear systems

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3D Imaging Sensing and Prediction technology of Large Component Surface with Multi-source Sensing 6

3D Imaging Sensing and Prediction Technology of Large Compon...

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6th Conference on Frontiers in Optical Imaging and technology: Applications of Imaging Technologies

作者： Sun, Jing Li, Lijuan Lin, Xuezhu Guo, Lili Liu, Yue Yan, Dongming Key Laboratory of Optoelectronic Measurement and Control and Optical Information Transmission Technology Ministry of Education College of Optoelectronic Engineering Changchun University of Science and Technology Changchun130022 China Zhongshan Research Institute of Changchun University of Science and Technology Guangdong Zhongshan528400 China

ISBN: (数字)9781510679757

ISBN: (纸本)9781510679740

In order to solve the problem that the surface deformation of large components cannot be photographed in real time due to the influence of assembly stress during assembly, a multi-source sensor surface deformation sensing and 3D imaging prediction technology for large components is proposed, which combined laser tracking, structured light detection and optical fiber sensing monitoring. Firstly, the multi-source sensor system is analyzed, and the multi-source sensor fusion sensing field is constructed. Secondly, the unified model of heterogeneous data is established to complete the accurate conversion of optical fiber monitoring wavelength to space point coordinates. Thirdly, multi-source data fusion is realized based on Gaussian process fusion algorithm to complete 3D imaging prediction of component surface deformation. Finally, a large skin component is taken as an example to simulate the assembly deformation experiment. The results show that the root-mean-square error is less than 0.1mm compared with the actual results. Based on the measured data of structured light scanning and multi-source sensing technology, a real-time sensing and prediction method for surface deformation imaging of large components is proposed. This method not only simplifies the scanning mode of structured light, but also provides a new idea for dynamic model building. © 2024 SPIE.

关键词： Forecasting

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