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CMAC-Based Sliding-Mode control for Large-Scale Fuzzy Descriptor Systems

CMAC-Based Sliding-Mode Control for Large-Scale Fuzzy Descri...

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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Zhong, Zhixiong Shao, Zhenghua Huan, Zhijie Wang, Xingyi Minjiang University Key Laboratory of Information Processing and Intelligent Control Fuzhou350121 China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin150080 China School of Electrical Engineering and Automation Xiamen University of Technology Xiamen361024 China

ISBN: (纸本)9781665481090

This paper addresses the problem of sliding-mode control for large-scale fuzzy descriptor systems subject to unknown uncertainties. First, a CMAC neural network is used to approximate the unknown uncertainties, and the CMAC-based sliding-mode controller is proposed. Then, a compensation technique is employed to eliminate the influence on the approximation error stemmed from CMAC model. We use the gradient-descent method to online tune the parameters of CMAC and the Lyapunov function is introduced to ensure the stability of the closed-loop control system and the CMAC's convergence. Finally, the effectiveness and correctness of the obtained theories are verified by the tracking control of multi-autonomous underwater vehicles (AUVs). © 2022 IEEE.

关键词： Autonomous underwater vehicles

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Deep Learning-based Serialized Model and Feature Extraction Algorithm for Solid Oxide Fuel Cell State Prediction 43

Deep Learning-based Serialized Model and Feature Extraction ...

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43rd Chinese control Conference, CCC 2024

作者： Wu, Jiajian Zhu, Kanglin Wu, Han Xiang, Guohui Li, Xi Huazhong University of Science and Technology School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry Hubei Wuhan China Shenzhen Huazhong University of Science and Technology Research Institute Guangdong Shenzhen China

ISBN: (纸本)9789887581581

Deep learning-based methods have shown their wide application prospects in the field of solid oxide fuel cell(SOFC) prediction. However, the irrationality of the prediction object and the lack of prediction accuracy have hindered the progress of the prediction methods for SOFC systems. Therefore, two algorithms are proposed in this study, a feature selection algorithm based on maximum information coefficient and Bayesian information criterion for identifying key variables that are sensitive to changes in the SOFC system, and a prediction model based on a genetic algorithm optimized for sequence to sequence architecture. The M/BIC algorithm reduces the number of features by 62.5% (from 40 to 15), which contributes to the acceleration of the algorithm training and the subsequent sensor layout optimization. The prediction model incorporates a two-dimensional convolutional neural network and a multi-head attention mechanism to capture more information in the input sequence, an encoder-decoder architecture and a Gated recurrent unit to better predict performance trends. Tests with real experimental data show significant changes in feature dimensionality reduction and prediction accuracy. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Dimensionality reduction

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Robust H∞ Attitude Stabilization for the Cluster Takeover of Non-cooperative Flexible Spacecraft 1

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29th International Conference on Computational and Experimental Engineering and Sciences, ICCES 2023

作者： Yue, Xiaokui Yang, Ziyu Yu, Hongyu Huang, Panxing Liu, Yuan National Key Laboratory of Aerospace Flight Dynamics School of Astronautics Northwestern Polytechnical University Xi’an710072 China Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control Engineering Beijing100094 China Beijing Institute of Remote Sensing Information Beijing100011 China

ISBN: (数字)9783031449475

ISBN: (纸本)9783031449468

In this paper, a cooperative control scheme based on the small spacecraft cluster is proposed for the takeover control of the failed flexible spacecraft in space. In order to overcome external disturbance, inertia uncertainty and controller gain perturbation, the controller spacecraft calculates the control torque which can stabilize the combined spacecraft in theory, and generates the desired control signal according to the robust H∞ non-fragile control law set in advance. Based on the communication topology, the actuator spacecraft restores the control signal according to the distributed control torque allocation scheme considering the saturation state of all reaction wheels, and implements it to achieve the attitude stabilization and vibration suppression of the combined spacecraft. Simulation results show that the distributed control torque allocation scheme can implement the desired control signal with relatively small error. Under the condition that the external disturbance, controller gain perturbation and inertia uncertainty coexist, the angle and angular velocity of the combined spacecraft can be stabilized quickly. Moreover, the vibration of the flexible appendages can also be suppressed effectively. During the whole takeover control process, the dynamic allocation scheme can always ensure that all reaction wheels of each actuator spacecraft never reach saturation. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Flexible spacecraft

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Spatial-Temporal-Rule-based Traffic Movement Status Interpretation at Intersections *

Spatial-Temporal-Rule-based Traffic Movement Status Interpre...

引用

2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Zhuang, Hanyang Gao, Liyang Qian, Yeqiang Wang, Chunxiang Yang, Ming University of Michigan Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9798350327182

Traffic light is the most significant component of road transportation. Traffic lights control the traffic movement at intersections by allowing the movement of some lanes and forbidding that of the others to ensure safety and efficiency. It is important for intelligent vehicles to understand the meaning of traffic lights. Conventional research works on traffic light detection and tracking consider each light independently, so the occlusion of some lights may mislead the decision of the vehicle. Since all traffic lights at an intersection work together, it is more essential to understand the traffic movement status controlled by the traffic lights rather than the perception of a single light. Therefore, this paper proposes a spatial-temporal-rule-based framework to interpret the current traffic movement status and predict the next status. The spatial information, including position and class, is obtained by traffic light detection. The temporal information is perceived by the proposed topologic-feature-based tracking method. The rule information is recognized by combination of spatial and temporal information. A dual-view camera system consisting of a telephoto camera and a wide-angle camera is adopted to ensure long perception distance and wide coverage simultaneously. The successful tracking of traffic lights from 200 m to 10 m away provides enough data to recognize the phase-change rule, which leads to correct interpretation and prediction. A customized dataset was collected, and experiments were conducted to illustrate the capability of the proposed method. © 2023 IEEE.

关键词： Cameras

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Formation control for Unmanned Surface Vehicles Based on Integrative APF and MPC

Formation Control for Unmanned Surface Vehicles Based on Int...

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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Li, Weilin Wu, Jing Long, Chengnian Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9781665481090

This paper takes the dual water jet propulsion USV as the research object, and studies formation obstacle avoidance optimization problem. An integrative APF algorithm is proposed to merge path planning and trajectory tracking into one optimization problem, where adaptive searching step is adopted to guarantee that the planned trajectory is reachable. In addition, a distance-triggered codesign of integrative APF and MPC is presented to maintain formation during the obstacle avoidance process. Finally, the results in MATLAB simulation demonstrate the validity and efficiency of the algorithm. © 2022 IEEE.

关键词： MATLAB

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An Assist-as-Needed Variable Admittance controller for Adaptive Support of Mobile Walking Assistive Robots 30

An Assist-as-Needed Variable Admittance Controller for Adapt...

引用

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

作者： Chen, Xinxing Zheng, Yue Su, Zongming Leng, Yuquan Huang, Jian Fu, Chenglong Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China Huawei Technologies Technology Planning Department Shenzhen China Key Laboratory for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9798350391916

Mobile walking assistive robots have been widely used for monitoring patients' gait patterns and providing support to prevent falls. Traditional approaches often separate the operational modes of these robots into human-following and supporting modes, which can lead to discontinuities in assistance and potentially compromise safety. This paper proposes a novel assist-as-needed control strategy that incorporates a Balance Index (BI) to dynamically adjust the robot's support based on the user's balance capability. The BI is calculated using the interaction force between the user and the robot along the z-axis and the gait symmetry index (GSI). The proposed variable admittance controller modifies its parameters based on the BI, ensuring seamless transitions between compliance and support modes. Experimental validation was conducted with a healthy subject walking both with and without a knee fixation brace. The results demonstrate that the robot provides minimal interference during natural gait and increased support during impaired gait, validating the effectiveness of the proposed control strategy in enhancing user safety and promoting natural walking patterns. © 2024 IEEE.

关键词： Assistive technology

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Research and Implementation of Chinese Resume Named Entity Recognition Method Based on BLDC 4

Research and Implementation of Chinese Resume Named Entity R...

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4th International Conference on Image processing and intelligent control, IPIC 2024

作者： Chen, Min Wei, Bin Yu, Hongzhi Wan, Fucheng Feng, Yulin Lu, Baoqing Key Laboratory of Linguistic and Cultural Computing Ministry of Education Northwest Minzu University Gansu Lanzhou730000 China Key Laboratory of Minzu Languages and Cultures Intelligent Information Processing Northwest Minzu University Gansu Province Gansu Lanzhou730000 China Lanzhou Technology and Business College Lanzhou China

ISBN: (纸本)9781510682313

Aiming at the semantic complexity and the difficulty of capturing long-distance dependencies in the task of named entity recognition in Chinese resume text, a BLDC (BERT-BiLSTM-Dense-CRF)-based named entity recognition method for Chinese resumes is investigated. The model first uses the pre-trained BERT-Base-Chinese model to obtain the semantic information of the text, then learns the contextual information of the sequence through the BiLSTM layer, followed by mapping the output of BiLSTM to the label space through the Dense layer, and finally uses the CRF layer to consider the dependencies between the labels for sequence annotation. Experimental results on public datasets show that the method outperforms other models in terms of precision, recall, and F1 value, and effectively improves the performance of named entity recognition in Chinese resume text. © 2024 SPIE.

关键词： Semantics

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Explicit Predictive control of Forward DC-DC Converter Based on an Input-Mapping Method

Explicit Predictive Control of Forward DC-DC Converter Based...

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第43届中国控制会议

作者： Xiang Gu Dewei Li Aoyun Ma Yaru Yu Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In the practical application of model predictive control in power electronics, both online computational burden and model accuracy are crucial. This paper presents an explicit model predictive control method based on input-mapping *** address the issue of parameter drift in the forward DC-DC converter system, the input-mapping method is introduced to compensate for model deviations using historical data. Firstly, the average model of the forward DC-DC converter system is introduced. For the control objective of voltage tracking, an explicit predictive control using the incremental model is ***, input-mapping method is integrated with explicit predictive control. During offline computation, analytical forms of the input-mapping combination coefficients and the optimal solution function of explicit model predictive control are *** computation of combination coefficients is conducted to obtain the optimal solution rapidly. The effectiveness of the proposed method is verified through simulations in MATLAB.

关键词： Forward DC-DC converter explicit model predictive control input-mapping method

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Cross-border Data Security Risk Analysis and Development Suggestions of the Protection Technologies for intelligent Connected Vehicles 5

Cross-border Data Security Risk Analysis and Development Sug...

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5th International Conference on information Science, Parallel and Distributed Systems, ISPDS 2024

作者： Huang, Xiaolong Xin, Chongshi Ji, Haojie Lu, Wangdong He, Peng Chen, Yupeng State Key Laboratory of Intelligent Vehicle Safety Technology Chongqing China Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science & Technology University Beijing China China Automotive Engineering Research Institute Co. Ltd Chongqing China

ISBN: (纸本)9798350352719

In recent years, intelligent connected vehicles (ICVs) have developed quickly and have been progressively introduced into the international market. Nevertheless, the operation of ICVs produces a large amount of important data coming from driving vehicle and necessitating cross-border transit. As the imperfections of the regulatory framework and the infancy of protective solutions for the ICV data, these data are vulnerable to the threats like eavesdropping and tampering during cross-border transmission. The private information, especially the data barred from leaving the country, will be probably leaked to other nations, endangering individual privacy and national security. Thus, the purpose of this manuscript is to analyze the security risks of cross-border data in ICVs and provide risk mitigation strategies. The legal requirements and pertinent cross-border materials need to be sorted out firstly to establish a thorough technical process for cross-border compliance of ICV data. Additionally, the ICV data risk analyses will be performed at every stage of the cross-border process. Furthermore, some efficient risk mitigation methods need to be offered to improve the security and dependability of the across-border data of ICVs. To address the problems associated with cross-border data pertaining to ICVs, a classification method for the cross-border data of ICVs will be presented according to current rules and data categorization schemes. Finally, this manuscript provides theoretical underpinnings and useful references for building a cross-border data security protection system, as well as a thorough analysis of the development patterns of cutting-edge technologies for cross-border data. © 2024 IEEE.

关键词： cross-border data data security protection technology risk analysis

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Cross-Modality Comprehensive Feature Aggregation Network for Road Scene Segmentation 8

Cross-Modality Comprehensive Feature Aggregation Network for...

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8th International Symposium on Computer Science and intelligent control, ISCSIC 2024

作者： Yang, Yale Zhang, Zihao Hou, Huifang Zhang, Wenwen Zhuang, Chunsheng Henan University of Technology College of Information Science and Engineering Zhengzhou China Henan University of Technology Key Laboratory of Grain Information Processing and Control Ministry of Education Henan Key Laboratory of Grain Photoelectric Detection and Control School of Artificial Intelligence and Big Data Zhengzhou China Data Henan University of Technology School of Artificial Intelligence and Big Zhengzhou China Henan Academy of Sciences Zhengzhou China

ISBN: (纸本)9798350380286

RGB-thermal semantic segmentation is a potential solution for reliable semantic scene understanding under adverse weather and complex lighting conditions. However, past studies have primarily focused on the design of fusion paradigms. Unfortunately, these methods have not fully considered the modality differences caused by different imaging mechanisms, thereby reducing the performance of pixel-level semantic analysis. In response to this issue, this paper proposes an innovative Cross-Modality Comprehensive Feature Aggregation Network (CFANet). This method first designs a Cross-Modality Feature Rectification Module (CFRM) to align modality differences;then, it constructs a Global-Local Fusion Module (GLF) to sharpen object edges and refine the segmentation map. Results on two urban scene understanding datasets demonstrate that CFANet can effectively aggregate multi-layer deep features and outperform existing advanced deep learning methods in scene understanding performance. © 2024 IEEE.

关键词： Semantic Segmentation

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