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第40届中国控制会议

作者： Chen Yan Chuan-Ke Zhang Xi-Zi Zhou School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Art and Design Wuhan University of Technology

This paper investigates the stability of linear systems with two additive time-varying delays. Firstly, an augmented Lyapunov-Krasovskii functional(LKF) is constructed by introducing a novel augmented term which contains the derivative of state vector into integral terms. Then the extended reciprocally convex matrix inequality together with the Wirtinger integral inequality is used to estimate the derivative of the proposed LKF. As a result, a stability criterion with less conservatism is established. Finally, the advantage of the stability criterion is demonstrated through a numerical example and the application of the stability criterion to stability analysis of load frequency control is illustrated.

关键词： linear system additive time-varying delays stability analysis reciprocally convex matrix inequality

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Automated Assembly by Two-Fingered Microhand for Fabrication of Soft Magnetic Microrobots

Automated Assembly by Two-Fingered Microhand for Fabrication...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Yue Zhao Xiaoming Liu Ruixi Wang Dan Liu Masaru Kojima Qiang Huang Tatsuo Arai Key Laboratory of Biomimetic Robots and Systems Ministry of Education State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing China School of Mechatronical Engineering Beijing Institute of Technology Beijing China Department of Intelligent Manufacturing Shenzhen International Graduate School Tsinghua University Shenzhen China Department of Materials Engineering Science Osaka University Osaka Japan Center for Neuroscience and Biomedical Engineering The University of Electro-Communications Tokyo Japan

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Micro-assembly is an emerging method to fabricate microrobots with multiple modules or particles. However, there is always a lack of a flexible and efficient method to freely create the desired magnetic soft microrobots. In this paper, an automated assembly system based on a two-fingered microhand is presented for fabricating magnetic soft microrobots. Our proposed system can automatically pick and place components to assemble microrobots with a two-fingered micromanipulator, and orient these components through an external magnetic field. The automated assembly has the advantages of high accuracy, high speed, and high success rate. It can endow magnetic microrobots with flexible material selection, arbitrary geometry design, and programable magnetization profile. We can make full use of this system to fabricate multiple magnetic soft microrobots. The experiment results demonstrate that this system can efficiently fabricate microrobots with excellent mechanical properties, which have application potential in robotics, biomedical engineering, and environmental governance.

关键词： Three-dimensional displays Shape Micromanipulators Magnetization Manuals Three-dimensional printing Soft magnetic materials

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Discretizing Continuous Action Space with Unimodal Probability Distributions for On-Policy Reinforcement Learning

arXiv

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arXiv 2024年

作者： Zhu, Yuanyang Wang, Zhi Zhu, Yuanheng Chen, Chunlin Zhao, Dongbin The Department of Control Science and Intelligent Engineering School of Management and Engineering Nanjing University Nanjing210093 China The Research Center for Novel Technology of Intelligent Equipment Nanjing University Nanjing210093 China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China

For on-policy reinforcement learning, discretizing action space for continuous control can easily express multiple modes and is straightforward to optimize. However, without considering the inherent ordering between the discrete atomic actions, the explosion in the number of discrete actions can possess undesired properties and induce a higher variance for the policy gradient estimator. In this paper, we introduce a straightforward architecture that addresses this issue by constraining the discrete policy to be unimodal using Poisson probability distributions. This unimodal architecture can better leverage the continuity in the underlying continuous action space using explicit unimodal probability distributions. We conduct extensive experiments to show that the discrete policy with the unimodal probability distribution provides significantly faster convergence and higher performance for on-policy reinforcement learning algorithms in challenging control tasks, especially in highly complex tasks such as Humanoid. We provide theoretical analysis on the variance of the policy gradient estimator, which suggests that our attentively designed unimodal discrete policy can retain a lower variance and yield a stable learning process. © 2024, CC BY.

关键词： Contrastive Learning

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A Preliminary Study on the Functional Coupling between Nerve and Blood Microcirculation for Applications in Rehabilitation Robots

A Preliminary Study on the Functional Coupling between Nerve...

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IEEE International Conference on Robotics and Biomimetics

作者： Qingge Li Yuanzhe Dong Yuxiang Zhang Xin Wang Naifu Jiang Jianping Huang Han Cui Lan Tian Yue Zheng Xiangxin Li Lin Wang Guanglin Li Wenyuan Liang Liang Peng Peng Fang CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China National Research Center for Rehabilitation Technical Aids Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Rehabilitation robots play an important role in the motor function rehabilitation for stroke survivors with hemiplegia. However, the rehabilitation effect of current robots is still limited partly because a single training of motor function can be strongly affected by the decreased blood supply function of the bedridden patients. This work proposed an approach to study the coupling relationship between the motor and blood supply functions by combining the synchronously recorded EEG and cerebral blood oxygen information, where the cerebrations in different movement paradigms were analyzed from an aspect of "functional coupling". The results show that the information of oxyhemoglobin concentration change (ΔHbO) can effectively indicate the cortex activation, and a stronger blood supply is needed in cortexes to perform body movements. The correlations within motor cortexes are significantly stronger than the ones between motor and prefrontal cortexes, and a higher resistance level of extremity training will cause stronger correlations. Calculation of transfer entropy (TE) shows that there exists a bidirectional information transmission between the electrophysiological and blood supply signals, and more information is transmitted always in the direction from ΔHbO to EEG than in the opposite direction. The information transmission or the coupling relationship can be significantly enhanced by extremity movements, and large TE values are achieved in the Theta, Beta and Gamma frequency bands of EEG that correspond to motor functions. This work has demonstrated the functional coupling between nerve and blood microcirculation, which would provide a technical guidance to improve the rehabilitation effect for current robot systems and have great application potentials.

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Psychological Resistance Recognition Based on Acoustic Features Extraction

Psychological Resistance Recognition Based on Acoustic Featu...

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Chinese automation Congress (CAC)

作者： Z. Lv Z. T Liu M. T. Han B. H. Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9781665426480

Psychological resistance can express the change of the client's psychological state, which is considered to be an important factor affecting psychological counseling. This paper proposed a method of psychological resistance recognition based on acoustic features extraction. The method includes three main steps, i.e., statistical acoustic feature extraction, feature selection, and classification. Our method uses statistical acoustic features to express psychological resistance, and analyzes the application value of high correlation features obtained from feature selection in the recognition of different psychological resistance. This method can be used to determine the high correlation features of psychological resistance adaptively, and avoid the deficiency of subjective judgment. A speech database of psychological resistance is built for research needs, in which three psychological consultants and four subjects are involved in psychological counseling with 1200 sentences in speech. The experimental results verified the effectiveness of our method.

关键词： Resistance Employee welfare Correlation automation Databases Psychology Feature extraction

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A Hybrid Modeling Method Based on Neural Networks and Its Application to Microwave Filter Tuning ⁎

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IFAC-PapersOnLine 2020年第2期53卷 176-181页

作者： Leyu Bi Weihua Cao Wenkai Hu Yan Yuan Min Wu School of Automation China University of Geosciences Wuhan Hubei 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei 430074 China

In performance tuning of many electromechanical devices, well-trained operators are in great demand. However, manual tuning is costly and time-consuming, and thus do not conform to the trend of smart manufacturing. Microwave filters are typical electromechanical devices. Their tuning performance is limited by low extraction accuracy and high dimensionality of circuit features. In this paper, a hybrid modeling method based on neural networks is proposed to get better tuning performance. First, a curve-shape-based modeling method using Convolutional Neural Networks is presented to bypass the cumbersome extraction of circuit features. Second, a multi-model optimized fusion model based on Elman Neural Networks is constructed to cope with the high-dimensional property of circuit features, and improve modeling accuracy. The effectiveness of the hybrid modeling method is demonstrated through experiments. It achieves better tuning performance with fewer samples compared with two single modeling methods.

关键词： intelligent Manufacturing Electromechanical Devices Tuning Hybrid Modeling Convolutional Neural Networks Optimized fusion modeling

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Distributed derivative-free learning method for stochastic optimization over a network with sparse activity

arXiv

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arXiv 2021年

作者： Li, Wenjie Assaad, Mohamad Zheng, Shiqi Paris Research Center Huawei Technologies France CentraleSupélec France Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences Wuhan430074 China

This paper addresses a distributed optimization problem in a communication network where nodes are active sporadically. Each active node applies some learning method to control its action to maximize the global utility function, which is defined as the sum of the local utility functions of active nodes. We deal with stochastic optimization problem with the setting that utility functions are disturbed by some non-additive stochastic process. We consider a more challenging situation where the learning method has to be performed only based on a scalar approximation of the utility function, rather than its closed-form expression, so that the typical gradient descent method cannot be applied. This setting is quite realistic when the network is affected by some stochastic and time-varying process, and that each node cannot have the full knowledge of the network states. We propose a distributed optimization algorithm and prove its almost surely convergence to the optimum. Convergence rate is also derived with an additional assumption that the objective function is strongly concave. Numerical results are also presented to justify our claim. Copyright © 2021, The Authors. All rights reserved.

关键词： Stochastic systems

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Quantized control for Highly Nonlinear Stochastic systems with Multiple Delays under DoS Attacks

Quantized Control for Highly Nonlinear Stochastic Systems wi...

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Chinese control Conference (CCC)

作者： Hairui Zhao Dongyan Chen Jun Hu School of Science Harbin University of Science and Technology Harbin China Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin University of Science and Technology Harbin China School of Automation Harbin University of Science and Technology Harbin China

In this paper, the quantized control problem is discussed for a class of highly nonlinear stochastic systems with multiple delays under the DoS attacks. The coefficients are allowed to be highly nonlinear, and the control input is subject to the quantization effects and the DoS attacks. The aim is to deal with the stabilization problem for unstable highly nonlinear stochastic systems with multiple delays. The $p-\text{th}$ moment exponential stability and almost surely exponential stability are discussed in light of the Lyapunov theory. Finally, an illustrative example is given to verify the validity of the theoretical results.

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Design of an Anti-Windup Equivalent-Input-Disturbance-Approach-Based control System

Design of an Anti-Windup Equivalent-Input-Disturbance-Approa...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Qicheng Mei Jinhua She Yosuke Nakanish School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Engineering Tokyo University of Technology Hachioji Tokyo Japan Graduate School of Environment and Energy Engineering Waseda University Shinjuku-ku Japan

ISBN: (纸本)9781665409858

This paper presents an anti-windup equivalent-input-disturbance (AEID) approach to eliminating both influences of disturbances and input saturation of a plant. The AEID approach has a conventional EID estimator and a newly added anti-windup structure. The EID estimator estimates the disturbances and uses estimated results to compensate for them. The anti-windup structure combats the influences of the input saturation. Numerical simulation verifies the effectiveness of the AEID approach.

关键词： Industrial electronics Simulation control systems Numerical simulation

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An ensemble model based on weighted support vector regression and its application in annealing heating process

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Science China(Information Sciences) 2019年第4期62卷 203-205页

作者： Yongyue ZHANG Weihua CAO Yali JIN Min WU School of Information Science and Engineering Central South University School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences

Dear editor,In the steel industry, the annealing heating production directly impacts the economic benefits of enterprises; hence, accurately predicting the required gas flow is very important [1]. On account of high equipment complexity, it costs lots of time for maintaining a traditional mechanism model at a good working condition; data-driven model, such

关键词： SVR An ensemble model based on weighted support vector regression and its application in annealing heating process

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