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第42届中国控制会议

作者： Kunpeng Zhang Chen Zhang Bo Yu Xu Zhang Yabin Gao Jianxing Liu Yue Zhao Department of Control Science and Engineering Harbin Institute of Technology

In this paper,an automatic blood sampling mechanism is proposed to reduce the working pressure of clinicians and the high risk of cross-infection caused by doctor-patient *** simulation environment for this mechanism is built via Gazebo in the Robot Operating System(ROS).Using Deep Deterministic Policy Gradient(DDPG) algorithm,the mechanism is trained to accomplish the blood sampling *** reward function and the neural network is adjusted to optimize the training *** prove that the trajectory of automatic blood sampling mechanism using DDPG algorithm has excellent performance in rapidity and stability,thus the effectiveness and usefulness of the designed system.

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Adaptive Faster Fixed-Time Nonsingular Terminal Sliding Mode control for Manipulator Systems

Adaptive Faster Fixed-Time Nonsingular Terminal Sliding Mode...

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2022 Chinese Automation Congress, CAC 2022

作者： Zhang, Kunpeng Liu, Zhuang Xu, Ruiqi Yu, Dongling Kong, Deshan Guan, Qichao Zhao, Yue State Grid Heilongjiang Electric Power Company Limited Yichun Power Supply Company Yichun China Harbin Institute of Technology Department of Control Science and Engineering Harbin China Southampton Ocean Engineering Joint Instituteg Harbin Engineering University Harbin China

ISBN: (纸本)9781665465335

In this paper, a controller which can achieve fixed-time convergence is studied for manipulator systems. Firstly, an adaptive neural network (ANN) is used to estimate the unknown parts and external disturbances of the system. Secondly, a piecewise sliding mode variable is used to realize the nonsingular control of the terminal sliding mode. Then, in order to improve the tracking speed of the manipulator system, a faster fixed-time control algorithm is designed, and the tracking error can converge within a faster fixed-time. Finally, the practicability of the proposed algorithm is verified by simulation. © 2022 IEEE.

关键词： Sliding mode control

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Fuzzy control design for time-delay systems under adaptive event-triggered mechanism

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Neural Computing and Applications 2024年第9期36卷 4727-4739页

作者： Du, Zhenbin Qu, Zifang Kao, Yonggui Wu, Zhaojing School of Computer and Control Engineering Yantai University Shandong Yantai264005 China School of Mathematics and Information Science Shandong Technology and Business University Shandong Yantai264005 China Department of Mathematics Harbin Institute of Technology Weihai264209 China School of Mathematics and Information Sciences Yantai University Shandong Yantai264005 China

This manuscript studies the fuzzy H∞ control design problem for nonlinear time-varying delay systems in fuzzy form via adaptive event-triggered mechanism. The fuzzy model and an adaptive event-triggered controller are connected in closed-loop form. A looped-functional is established to conduct stability analysis, and the main feature of this functional can fully reflect the sampling feature of control systems. Thus, the achieved results are less conservative. The Wringter inequality is also used to further relax stability analysis. Finally, sufficient conditions are achieved for the existence of event-triggered fuzzy controller, and the resulting closed-loop system reaches an H∞ control performance. Two examples verify the efficiency of the presented control strategy. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2023.

关键词： Time delay

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An improved classification method of ultrasonic thyroid standard planes based on Bayesian optimization of multi-feature parameters for portable application

An improved classification method of ultrasonic thyroid stan...

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第42届中国控制会议

作者： Xinran Li Xin Zhang Chenyang Fan Yi Shen Department of Control Science and Engineering Harbin Institute of Technology School of Mathematics Harbin Institute of Technology

In recent years,computer aided technology is increasingly applied to the classification of thyroid ultrasonic planes for calculating the thyroid volume,and then the disease can be diagnosed by its ***,these methods requiring greater computational power are not suitable for the portable ultrasound system with limited *** on Bayesian optimization of multi-feature parameters,an improved classification method of ultrasonic thyroid planes is proposed in this paper for low computational complexity with a high classification *** Binary Patterns(LBP) feature and Gray Level Co-occurrence Matrix(GLCM) feature are selected by the analysis of image texture information,and then the combined feature is utilized to investigate the effectiveness of different ***,Bayesian optimization is employed to obtain the optimal parameters of the combined feature for improving classification results,and the accuracy can reach up to 96.81%.The results clearly illustrate that the improved method is effective in classifying the ultrasonic thyroid planes under a low computational complexity.

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Sign consensus of heterogeneous linear multi-agent systems without an explicit leader 41

Sign consensus of heterogeneous linear multi-agent systems w...

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第41届中国控制会议

作者： Yihan Meng Shimin Wang Shuai Liu Hongwei Zhang School of Mechanical Engineering and Automation Harbin Institute of Technology Department of Chemical Engineering Queen's University School of Control Science and Engineering Shandong University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper investigates leaderless output sign consensus of heterogeneous linear multi-agent systems over fixed directed signed *** multi-agent system can synchronize in the same sign concurrently with time-varying values without an explicit *** on the assumption that the adjacency matrix of the signed graph is eventually positive,a virtual leader is constructed by utilizing a distributed sign *** virtual leader is not pre-specified but arises from the graph topology and the initial states of the *** light of this distributed sign observer,we propose a state feedback controller that drives the outputs of such multi-agent systems to reach sign consensus.

关键词： Distributed observer Multi-agent system Sign consensus Signed graph

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ACIGS: An automated large-scale crops image generation system based on large visual language multi-modal models

ACIGS: An automated large-scale crops image generation syste...

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IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON)

作者： Bolong Liu Hao Zhang Jie Liu Qiang Wang Department of Control Science and Engineering Harbin Institute of Technology Harbin China Department of Computer Science and Technology Harbin Institute of Technology (ShenZhen) ShenZhen China

Smart agriculture requires an extensive convergence of information technology and agriculture. Attaining intelligence mandates an enormous amount of data to train models. However, it is challenging to acquire a large number of crop image data, limiting the application and growth of computer vision technology in agriculture. To address this problem, we designed a crop image generation system that combines a large language model with visual language multi-modal large models to augment the scale, variety, and resolution of crop image data. First, the system inputs existing real crop images into the visual language multimodal model to extract features and represent crop images in text form. Then, the system passes the crop text representation to the language model for cleaning and processing, which generates prompts to create crop images. The prompts are input into the visual language multi-modal model to generate crop images based on text representation of crops. The resulting crop images undergo image quality evaluation in the visual language multimodal model, and high-quality crop images are saved to the crop image dataset based on the quality evaluation. These steps lead to the formation of the final generated crop image dataset. The experimental results indicate that the crop images generated using the proposed system are similar to but different from the example images. This characteristic enables the expansion of crop data while circumventing redundancy and allowing for resolution control, which is crucial for dense segmentation tasks. Using this method, the existing data can be enlarged up to 7.5 times.

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High biomass yields of Chlorella protinosa with efficient nitrogen removal from secondary effluent in a membrane photobioreactor

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Journal of Environmental sciences 2024年第12期146卷 272-282页

作者： Min Yang Zhen Liu Aijie Wang Ingmar Nopens Hairong Hu Hong Chen School of Civil and Environmental Engineering Harbin Institute of Technology(Shenzhen)Shenzhen 518055China Key Laboratory of Dongting Lake Aquatic Eco-Environmental Control and Restoration of Hunan Province Changsha 410114China BIOMATH Department of Data Analysis and Mathematical ModellingGhent UniversityGent B 9000Belgium Key Laboratory of Environmental Biotechnology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China School of Materials Science and Engineering Hunan University of Science and TechnologyXiangtan 411201China

Further treatment of secondary effluents before their discharge into the receiving water bodies could alleviate water *** this study,the Chlorella proteinosa was cultured in a membrane photobioreactor to further remove nitrogen from the secondary *** effect of hydraulic retention time(HRT)on microalgae biomass yields and nutrient removal was *** results showed that soluble algal products concentration reduced in the suspension at low HRT,thereby alleviating microalgal growth *** addition,the lower HRT reduced the nitrogen limitation for Chlorella proteinosa’s growth through the phase-out of nitrogen-related functional *** a result,the productivity for Chlorella proteinosa increased from 6.12 mg/L/day at an HRT of 24 hr to 20.18 mg/L/day at an HRT of 8 *** highest removal rates of 19.7 mg/L/day,23.8 mg/L/day,and 105.4 mg/L/day were achieved at an HRT of 8 hr for total nitrogen(TN),ammonia,and chemical oxygen demand(COD),***,in terms of removal rate,TN and COD were the largest when HRT is 24 hr,which were 74.5%and 82.6%*** maximum removal rate of ammonia nitrogen was 99.2%when HRT was 8 hr.

关键词： Chlorella MPBR Fouling HRT SAP Nutrient

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Adaptive Sliding-Mode Fault Tolerant control for Delayed Nonlinear Systems with Actuator Fault 7

Adaptive Sliding-Mode Fault Tolerant Control for Delayed Non...

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7th International Conference on control science and Systems engineering, ICCSSE 2021

作者： Zhang, Hongxu Hu, Jun Yu, Xiaoyang Chen, Dongyan Harbin University of Science and Technology School of Measurement Control Technology Communication Engineering Department of Mathematics Harbin China Harbin University of Science and Technology Department of Mathematics Harbin China Harbin University of Science and Technology School of Measurement Control Technology Communication Engineering Harbin China

ISBN: (纸本)9781665444057

This paper focuses on the sliding mode fault-tolerant control (SMFTC) problem for a class of delayed nonlinear systems in presence of actuator fault and nonlinear input. Firstly, the augmented strategy involving system state, actuator fault and external disturbance is constructed, and then the fault-tolerant observer is designed accordingly. An SMFTC law ensuring the asymptotical stability of the reduce-order estimation error is provided subsequently. To further illustrate the system performance, a new sliding function with respect to decomposed signal is constructed and the asymptotically stability of sliding motion is analyzed. Moreover, a novel adaptive-based sliding mode controller is presented to steer the system state onto the sliding manifold. Finally, a verification example is considered to demonstrate the usefulness of the proposed SMFTC approach. © 2021 IEEE.

关键词： Sliding mode control

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DESKO: STABILITY-ASSURED ROBUST control OF NONLINEAR SYSTEMS WITH A DEEP STOCHASTIC KOOPMAN OPERATOR 10

DESKO: STABILITY-ASSURED ROBUST CONTROL OF NONLINEAR SYSTEMS...

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10th International Conference on Learning Representations, ICLR 2022

作者： Han, Minghao Euler-Rolle, Jacob Katzschmann, Robert K. Department of Control Science and Engineering Harbin Institute of Technology China Soft Robotics Lab ETH Zurich Switzerland

The Koopman operator theory linearly describes nonlinear dynamical systems in a high-dimensional functional space and it allows to apply linear control methods to highly nonlinear systems. However, the Koopman operator does not account for any uncertainty in dynamical systems, causing it to perform poorly in real-world applications. Therefore, we propose a deep stochastic Koopman operator (DeSKO) model in a robust learning control framework to guarantee stability of nonlinear stochastic systems. The DeSKO model captures a dynamical system's uncertainty by inferring a distribution of observables. We use the inferred distribution to design a robust, stabilizing closed-loop controller for a dynamical system. Modeling and control experiments on several advanced control benchmarks show that our framework is more robust and scalable than state-of-the-art deep Koopman operators and reinforcement learning methods. Tested control benchmarks include a soft robotic arm, a legged robot, and a biological gene regulatory network. We also demonstrate that this robust control method resists previously unseen uncertainties, such as external disturbances, with a magnitude of up to five times the maximum control input. Our approach opens up new possibilities in learning control for high-dimensional nonlinear systems while robustly managing internal or external uncertainty. © 2022 ICLR 2022 - 10th International Conference on Learning Representationss. All rights reserved.

关键词： Dynamical systems

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Contrastive Augmented Graph2Graph Memory Interaction for Few Shot Continual Learning

arXiv

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arXiv 2024年

作者： Qi, Biqing Gao, Junqi Chen, Xingquan Li, Dong Liu, Jianxing Wu, Ligang Zhou, Bowen Department of Control Science and Engineering Harbin Institute of Technology Harbin China Department of Electronic Engineering Tsinghua University Beijing China School of Mathematics Harbin Institute of Technology Harbin China Frontis.AI Beijing China

Few-Shot Class-Incremental Learning (FSCIL) has gained considerable attention in recent years for its pivotal role in addressing continuously arriving classes. However, it encounters additional challenges. The scarcity of samples in new sessions intensifies overfitting, causing incompatibility between the output features of new and old classes, thereby escalating catastrophic forgetting. A prevalent strategy involves mitigating catastrophic forgetting through the Explicit Memory (EM), which comprise of class prototypes. However, current EM-based methods retrieves memory globally by performing Vector-to-Vector (V2V) interaction between features corresponding to the input and prototypes stored in EM, neglecting the geometric structure of local features. This hinders the accurate modeling of their positional relationships. To incorporate information of local geometric structure, we extend the V2V interaction to Graph-to-Graph (G2G) interaction. For enhancing local structures for better G2G alignment and the prevention of local feature collapse, we propose the Local Graph Preservation (LGP) mechanism. Additionally, to address sample scarcity in classes from new sessions, the Contrast-Augmented G2G (CAG2G) is introduced to promote the aggregation of same class features thus helps few-shot learning. Extensive comparisons on CIFAR100, CUB200, and the challenging ImageNet-R dataset demonstrate the superiority of our method over existing methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Geometry

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