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Adaptive fuzzy asymptotic control design for MIMO nonlinear systems with state constraints

Journal of control and Decision 2023年第4期10卷 610-623页

作者： Yongchao Liu Bowen Zeng Qidan Zhu Lipeng Wang Institute of Complexity Science School of AutomationQingdao UniversityQingdaoPeople’s Republic of China Shandong Key Laboratory of Industrial Control Technology QingdaoPeople’s Republic of China College of Intelligent Systems Science and Engineering Harbin Engineering UniversityHarbinPeople’s Republic of China

This paper addresses the asymptotic control problem of uncertain multi-input and multi-output(MIMO)nonlinear *** considered MIMO systems contain unknown virtual control coefficients(UVCCs)and state *** Lyapunov function by associating with the lower bounds of UVCCs is presented to counteract the adverse effect deriving from *** state constraints are ensured by utilising the barrier Lyapunov ***,the asymptotic tracking controller is recursively constructed by combining the backstepping technique with fuzzy logic *** remarkable character of the designed controller is that the asymptotic tracking performance can be achieved by introducing some smooth functions into adaptive backstepping *** contrast to the existing results,the conditions on the UVCCs are ***,the new control design is illustrated by a practical example.

关键词： Asymptotic tracking control state constraints bound estimation method nonlinear systems

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A Framework of LSTM Neural Network Model in Multi-Time Scale Real-Time Prediction of Ship Motions in Head Waves

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船舶力学 2024年第12期28卷 1803-1819页

作者： CHEN Zhan-yang ZHAN Zheng-yong CHANG Shao-ping XU Shao-feng LIU Xing-yun Department of Ocean Engineering Harbin Institute of Technology at WeihaiWeihai 264209China State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentDalian University of TechnologyDalian 116024China Flight Control System Department AVIC Xi'an Flight Automatic Control Research InstituteXi'an 710065China

Ship motions induced by waves have a significant impact on the efficiency and safety of offshore ***-time prediction of ship motions in the next few seconds plays a crucial role in performing sensitive ***,the obvious memory effect of ship motion time series brings certain difficulty to rapid and accurate ***,a real-time framework based on the Long-Short Term Memory(LSTM)neural network model is proposed to predict ship motions in regular and irregular head waves.A 15000 TEU container ship model is employed to illustrate the proposed *** numerical implementation and the real-time ship motion prediction in irregular head waves corresponding to the different time scales are carried out based on the container ship *** related experimental data were employed to verify the numerical simulation *** results show that the proposed method is more robust than the classical extreme short-term prediction method based on potential flow theory in the prediction of nonlinear ship motions.

关键词： deep learning LSTM ship motion real-time prediction irregular waves

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Microstructure and properties of AgCu/2 wt%Ag-added Sn-Pb solder/CuBe joints fabricated by vapor phase soldering

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Rare Metals 2022年第6期41卷 1983-1988页

作者： Wei Liu Rong An Ying Ding Chun-Qing Wang Yan-Hong Tian Kun Shen State Key Laboratory of Welding and Joining Harbin Institute of TechnologyHarbin 150001China School of Engineering and Physical Sciences Heriot-Watt UniversityEdinburgh EH144ASUK Key Laboratory of Miero-systems and Micro-structures Manufacturing Ministry of Education.Harbin Institute of TechnologyHarbin 150001China Beijing Institute of Control Engineering Beijing 100190China

The purpose of this paper is to investigate the effect of 2 wt%Ag addition in Sn-Pb eutectic solder on microstructure and mechanical properties of AgCu/solder/CuBe joint fabricated by vapor phase soldering.63Sn37Pb and 62Sn36Pb2Ag solder pastes were used to join Cu(1.7 wt%-2.5 wt%)Be and Ag(2 wt%-5 wt%)Cu *** fracture modes are observed in 62Sn36Pb2Ag and 63Sn37Pb joints after lateral shear tests at room temperature or 120℃,and shear forces of 62Sn36Pb2Ag joints are far higher than those of 63Sn37Pb *** obvious difference is observed in morphology and thickness of intermetallic compounds(IMCs)at interfaces of the 63Sn37Pb and 62Sn36Pb2Ag *** the two kinds of joints,for-mation of big blocky or plate-like Ag_(3)Sn is ***,many Ag_(3)Sn IMCs particles(1-3 μm in width)in isolated and dispersed distribution are observed within 62Sn36Pb2Ag *** Ag3Sn particles are responsible for the better mechanical properties of 62Sn36Pb2 Ag joints than those of 63Sn37Pb *** results present in this paper may provide a guide for restraining formation of big blocky or plate-like Ag_(3) Sn in joints with Ag pads or thick Ag surface finish on pads by utilizing vapor phase soldering process,and improving mechanical properties of Cu/SnPb/Ag joints by adding Ag in SnPb eutectic solder.

关键词： Microstructure Mechanical property 62Sn36Pb2Ag solder Ag,Sn Vapor phase soldering

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L2COcc: Lightweight Camera-Centric Semantic Scene Completion via Distillation of LiDAR Model

arXiv

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arXiv 2025年

作者： Wang, Ruoyu Ma, Yukai Yao, Yi Tao, Sheng Li, Haoang Zhu, Zongzhi Liu, Yong Zuo, Xingxing Institute of Cyber-Systems and Control Zhejiang University Hangzhou China School of Computation Information and Technology Technical University of Munich Munich Germany Zhejiang Guoli Security Technology Co. Ltd. Ningbo China State Key Laboratory of Industrial Control Technology China

Semantic Scene Completion (SSC) constitutes a pivotal element in autonomous driving perception systems, tasked with inferring the 3D semantic occupancy of a scene from sensory data. To improve accuracy, prior research has implemented various computationally demanding and memory-intensive 3D operations, imposing significant computational requirements on the platform during training and testing. This paper proposes L2COcc, a lightweight camera-centric SSC framework that also accommodates LiDAR inputs. With our proposed efficient voxel transformer (EVT) and cross-modal knowledge modules, including feature similarity distillation (FSD), TPV distillation (TPVD) and prediction alignment distillation (PAD), our method substantially reduce computational burden while maintaining high accuracy. The experimental evaluations demonstrate that our proposed method surpasses the current state-of-the-art vision-based SSC methods regarding accuracy on both the SemanticKITTI and SSCBench-KITTI-360 benchmarks, respectively. Additionally, our method is more lightweight, exhibiting a reduction in both memory consumption and inference time by over 23% compared to the current state-of-the-arts method. Code is available at our project page: https://***/L2COcc/. © 2025, CC BY.

关键词： Benchmarking

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A BERT-Based Named Entity Recognition Method of Warm Disease in Traditional Chinese Medicine

A BERT-Based Named Entity Recognition Method of Warm Disease...

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IEEE Conference on industrial Electronics and Applications (ICIEA)

作者： Zijun Song Wen Xu Zhitao Liu Liang Chen Hongye Su Polytechnic Institute Zhejiang University Hangzhou China Binzhou Medical University Yantai China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

Traditional Chinese medicine (TCM) documents have been handed down through the ages, containing rich theoretical knowledge and clinical experience. These unstructured data are the foundation for building the digital knowledge system of TCM. However, written in ancient Chinese, the TCM books have complex grammatical rules and terms which are different from modern medicine, inducing difficulty in entity annotation and recognition. In order to solve the problem of lacking labeled data, we construct a dataset with Wenbing Tiaobian, a classic work of TCM on the warm disease, identify six entities and annotate the book with the BIOES method. The BERT-BILSTM-CRF model is used to conduct experiments on the dataset with an F1 value of 91.4%. The results verify the effectiveness of the model in NER tasks and advance the construction of knowledge graphs in TCM.

关键词：

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Unimodular Complete Complementary Sequence with Optimal Trade-off between Auto- and Cross-ambiguity Functions for MIMO Radars

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-11页

作者： Li, Yuke Zhou, Yongxing Li, Xueru Wang, Junbo Wang, Yutong Fan, Lili Wang, Fei-Yue Waytous Co. Ltd. Beijing China Consumer BG Huawei Technologies Co. Ltd Beijing China School of Software Northwestern Polytechnical University Xi'an China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Beijing China School of Information and Electronics Beijing Institute of Technology Beijing China

It is difficult to design unimodular sequences with both good auto-ambiguity functions (AF) and cross-ambiguity functions (CAF), due to its nonconvex and higher cardinality property. To address this problem, we propose a Pareto optimization framework to reach an optimal tradeoff between AF and CAF. Besides, we also propose a novel convolution-based multi-objective optimization algorithm to optimize the conventional metrics including peak sidelobe level (PSL) and integrated sidelobe level (ISL). In this way, the generated sequences are Doppler resilient with the desired shape of aperiodic or periodic AFs. Compared with the state-of-the-art methods, simulation experimental results indicate the PSL metric of AF and CAF can be both suppressed to -72dB under the same system parameters, obtaining a minimum of 7 dB gain. IEEE

关键词： Multiobjective optimization

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OTFS Modulation and PAPR Reduction for IoT-Railways

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China Communications 2023年第1期20卷 102-113页

作者： Huichao Shang Ruifeng Chen Haoxiang Zhang Guoyu Ma Ruisi He Bo Ai Zhangdui Zhong State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong UniversityBeijing 100044China Institute of Computing Technologies China Academy of Railway Sciences Co.Ltd.Beijing 100081China China Academy of Industrial Internet Ministry of Industry and Information TechnologyBeijing 100804China

The internet of things(IoT)has been widely considered to be integrated with high-speed railways to improve safety and *** is important to achieve reliable communication in IoT for railways(IoT-R)under high mobility scenarios and strict energy *** time frequency space(OTFS)modulation is a two-dimensional modulation technique that has the potential to overcome the challenges in high Doppler *** addition,OTFS can have lower peak-to-average power ratio(PAPR)compared to orthogonal frequency division multiplexing,which is especially important for the application of ***,OTFS modulation for IoT-R is investigated in this *** order to decrease PAPR of OTFS and promote the application of OTFS modulation in IoT-R,the peak windowing technique is used in this *** technique can reduce the PAPR of OTFS by reducing the peak power and does not require multiple *** impacts of different window functions,window sizes and clipping levels on PAPR and bit error rate of OTFS are simulated and *** simulation results show that the peak windowing technique can efficiently reduce the PAPR of OTFS for IoT-R.

关键词： internet of things for railways(IoT-R) orthogonal time frequency space(OTFS) peak-toaverage power ratio(PAPR) peak windowing

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The Research on Sheet Metal Part Recognition technology Based on Improved Mask R-CNN 5

The Research on Sheet Metal Part Recognition Technology Base...

引用

5th International Conference on Machine Learning and Computer Application, ICMLCA 2024

作者： Liu, Mingfei Liu, Jun Zhou, Kecheng Wang, Jian School of Computer Science and Technology Shenyang University of Chemical Technology Key Laboratory of Industrial Intelligence Technology on Chemical Process Liaoning Province Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Chinese Academy of Sciences Shenyang110016 China

ISBN: (纸本)9798331530334

The visual recognition of sheet metal parts is a crucial component of industrial automation sorting, particularly under complex lighting and background interference conditions. To enhance the accuracy of sheet metal part recognition, this paper curates a dataset of sheet metal parts acquired by an intelligent light field image sensor and proposes a visual recognition model, PA-CBAM, based on an improved Mask R-CNN. By improving the original feature pyramid FPN and introducing the Convolutional Block Attention Module (CBAM), the model enhances multi-scale feature fusion and the focus on key features: (1) Bottom up paths and shortcut connections have been added between different layers of the traditional FPN feature pyramid, thereby improving multi-scale object detection capability. (2) CBAM further optimizes the model's channel and spatial attention mechanisms, effectively enhancing the capture of edge details and the suppression of background noise. Experimental results show that the proposed PA-CBAM model significantly improves detection and segmentation performance compared to traditional methods, particularly in terms of edge recognition accuracy for sheet metal parts under complex lighting conditions. © 2024 IEEE.

关键词： Sheet metal

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Dynamic Collision Avoidance Using Velocity Obstacle-Based control Barrier Functions

arXiv

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arXiv 2025年

作者： Huang, Jihao Zeng, Jun Chi, Xuemin Sreenath, Koushil Liu, Zhitao Su, Hongye State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Institute of Intelligence Science and Engineering Shenzhen Polytechnic University Shenzhen China Hybrid Robotics Group The Department of Mechanical Engineering UC Berkeley United States

Designing safety-critical controllers for acceleration-controlled unicycle robots is challenging, as control inputs may not appear in the constraints of control Lyapunov functions (CLFs) and control barrier functions (CBFs), leading to invalid controllers. Existing methods often rely on state-feedback-based CLFs and high-order CBFs (HOCBFs), which are computationally expensive to construct and fail to maintain effectiveness in dynamic environments with fast-moving, nearby obstacles. To address these challenges, we propose constructing velocity obstacle-based CBFs (VOCBFs) in the velocity space to enhance dynamic collision avoidance capabilities, instead of relying on distance-based CBFs that require the introduction of HOCBFs. Additionally, by extending VOCBFs using variants of VO, we enable reactive collision avoidance between robots. We formulate a safety-critical controller for acceleration-controlled unicycle robots as a mixed-integer quadratic programming (MIQP), integrating state-feedback-based CLFs for navigation and VOCBFs for collision avoidance. To enhance the efficiency of solving the MIQP, we split the MIQP into multiple sub-optimization problems and employ a decision network to reduce computational costs. Numerical simulations demonstrate that our approach effectively guides the robot to its target while avoiding collisions. Compared to HOCBFs, VOCBFs exhibit significantly improved dynamic obstacle avoidance performance, especially when obstacles are fast-moving and close to the robot. Furthermore, we extend our method to distributed multi-robot systems. Copyright © 2025, The Authors. All rights reserved.

关键词： state feedback

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Decentralized Zeno-Free Event-Triggered control For Multiple Networks Subject to Stochastic Network Delays and Poisson Pulsing Attacks

arXiv

引用

arXiv 2024年

作者： Zhang, Dandan Jin, Xin Su, Hongye The State Key Laboratory of Industrial Control Technology The Institute of Cyber-Systems and Control The College of Control Science and Engineering Zhejiang University Hangzhou310027 China The Research Institute of Intelligent Complex Systems Fudan University Shanghai200433 China The Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China

By designing the decentralized time-regularized (Zeno-free) event-triggered strategies for the state-feedback control law, this paper considers the stochastic stabilization of a class of networked control systems, where two sources of randomness exist in multiple decentralized networks that operate asynchronously and independently: the communication channels are constrained by the stochastic network delays and also by Poisson pulsing denial-of-service (Pp-DoS) attacks. The time delay in the network denotes the length from a transmission instant to the corresponding update instant, and is supposed to be a continuous random variable subject to certain continuous probability distribution;while the attacks' cardinal number is a discrete random variable supposed to be subject to Poisson distribution, so the inter-attack time, i.e., the time between two consecutive attack instants, is subject to exponential distribution. The considered system is modeled as a stochastic hybrid formalism, where the randomness enters through the jump map into the reset value (the inter-attack time directly related) of each triggered strategy. By only sampling/transmitting state measurements when needed and simultaneously by taking the specific medium access protocols into account, the designed event-triggered strategies are synthesized in a state-based and decentralized form, which are robust (tolerable well) to stochastic network delays, under different tradeoff-conditions between the minimum inter-event times, maximum allowable delays (i.e., potentially tolerable delays) and the frequencies of attacks. Using stochastic hybrid tools to combine attack-active parts with attack-over parts, the designed triggered strategies, if designed well according to the actual system needs, can tolerate (be resilient to) the Pp-DoS attacks and stochastic network delays without jeopardizing the stability and Zeno-freeness, which is verified by the robust global attitude stabilization of flexible combined ro

关键词： Networked control systems

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