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第40届中国控制会议

作者： Mengyang Yao Yi Liu Chi Xu School of Automation China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

Smart wheelchair plays an important role in rehabilitation training and daily movement of people with high mobility *** ensure that the smart wheelchair can operate stably in an unfamiliar environment,it is necessary to solve the problems of locating,mapping and motion *** the complex indoor environment of rehabilitation training and the wheelchair model,we propose a new smart wheelchair system *** on Simultaneous Localization and Mapping（SLAM） technology,location and mapping can be obtained through the Rao-Blackwellized Particle Filters（RBPF） *** integrate the sensor data into the proposal distribution to solve the particle degradation problem of RBPF and use selective resampling to improve the algorithm *** to the wheelchair’s own location and the surrounding environment map,global path planning and local real-time path planning are used to complete the motion *** show that the smart wheelchair system we proposed can operate robustly and quickly in a complex indoor environment.

关键词： Smart wheelchair Rehabilitation training SLAM Motion planning

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Designing edge-based and node-based fully distributed algorithms for aggregative games with the adaptive technique

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Automatica 2025年 179卷

作者： Dong Wang Mingfei Chen Jie Lian Peng Lin Zhengguang Wu Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education School of Control Science and Engineering Dalian University of Technology Dalian China School of Automation Central South University Changsha China Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

This paper focuses on aggregative games with local feasibility decision sets in a partial-decision information scenario. To seek the Nash equilibrium in a fully distributed manner, adaptive algorithms with edge-based and node-based control gains are designed. In the edge-based adaptive algorithm, an auxiliary dynamics is developed with the consensus protocol and adaptively adjusts the edges’ weights. In the node-based adaptive algorithm, fully distributed decision-seeking is achieved by dynamically modifying the player’s weight based on the overall consensus error. By virtue of the designed adaptive parameters, players update decisions without any global information. Utilizing Lyapunov stability theory and the comparison lemma, the proposed algorithms converge exponentially to a small neighborhood of the Nash equilibrium. Furthermore, the proposed adaptive algorithms are extended to the prescribed-time case by combining the prescribed-time gain function and exponential adaptive parameters. Finally, numerical simulations are presented to demonstrate the effectiveness of the proposed algorithms.

关键词： Adaptive technique Aggregative games Exponential convergence Fully distributed Nash equilibrium Prescribed-time convergence

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A Cyclic Small Phase Theorem

arXiv

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arXiv 2023年

作者： Chen, Chao Chen, Wei Zhao, Di Chen, Jianqi Qiu, Li KU Leuven Leuven3001 Belgium The Department of Mechanics and Engineering Science State Key Laboratory for Turbulence and Complex Systems Peking University Beijing100871 China The Department of Control Science and Engineering Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai200092 China The Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

This paper introduces a brand-new phase definition called the segmental phase for multi-input multi-output linear time-invariant systems. The underpinning of the definition lies in the matrix segmental phase which, as its name implies, is graphically based on the smallest circular segment covering the matrix normalized numerical range in the unit disk. The matrix segmental phase has the crucial product eigen-phase bound, which makes itself stand out from several existing phase notions in the literature. The proposed bound paves the way for stability analysis of a cyclic feedback system consisting of multiple subsystems. A cyclic small phase theorem is then established as our main result, which requires the loop system phase to lie between −π and π. The proposed theorem complements a cyclic version of the celebrated small gain theorem. In addition, a generalization of the proposed theorem is made via the use of angular scaling techniques for reducing conservatism. Copyright © 2023, The Authors. All rights reserved.

关键词： Linear time-invariant system

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Finite-time Stability of Networked Predictive control systems with Uncertainties

Finite-time Stability of Networked Predictive Control System...

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第三十九届中国控制会议

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

In this paper, the problem of finite-time stability is studied for a class of networked predictive control systems with parameter uncertainties. Firstly, both the modelling uncertainties and the network-induced delays are considered. A networked predictive control scheme is proposed to actively compensate the network-induced delays. Secondly, a sufficient condition is given to ensure the finite-time stability of the augmented closed-loop system with time delay, where both bilinear matrix inequality and linear matrix inequality conditions are derived with the help of Lyapunov stability theorem. At the same time, an alternate algorithm is designed to obtain the gain matrices of observer and controller from bilinear matrix inequality and linear matrix inequality. Finally, a numerical example is given to confirm the feasibility of the proposed results.

关键词： Networked predictive control finite-time stability parameter uncertainty network-induced delay bilinear matrix inequality

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Design of a novel flexible assistive hand exoskeleton

Design of a novel flexible assistive hand exoskeleton

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Guotao Li Long Cheng Zhengrun Gao Jilong Lu Yanjiang Zhao State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China The National Clinical Research Center for Aging and Medicine Fudan University Shanghai China Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education Harbin University of Science and Technology Harbin China Intelligent Machine Institute Harbin University of Science and Technology Harbin China

ISBN: (纸本)9781665465373

Hand paralysis caused by stroke, spinal cord injury, or neurological trauma has a significant impact on the independence and quality of life of the patients. The hand exoskeleton can provide hand assistance and improve the patient’s grasp. In this article, a novel wearable flexible hand exoskeleton is proposed to assist users in activities of daily life. To create a simple and lightweight assistive hand exoskeleton, 3D printing is used to manufacture most of the components, and a remote drive system is designed to reduce the weight of the hand exoskeleton. A ball pair device and a slider device are used to ensure the freedom of the thumb and the adaptability of the hand exoskeleton to different hand sizes. Finally, the experiments are conducted to verify that the hand exoskeleton can achieve motion assistance.

关键词： Exoskeletons Thumb Metals Stroke (medical condition) Three-dimensional printing Motion capture Paralysis

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State Estimation for Discrete Neural Networks with False Data Injection Attacks under Weighted Try-Once-Discard Protocol

State Estimation for Discrete Neural Networks with False Dat...

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第三十九届中国控制会议

作者： Dianhong Hou Dongyan Chen Ning Yang School of Science Harbin University of Science and Technology Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin University of Science and Technology

This paper investigates the state estimation problem for a class of discrete neural networks with time-varying delays and false data injection attacks under weighted try-once-discard（WTOD） protocol. The false data injection attacks are modelled by using the Bernoulli distributed random variable. The measurements are transmitted according to the WTOD protocol in order to reduce unnecessary data transmission and alleviate the bandwidth pressure. A state estimator is designed based on the obtained measurement. By utilizing Lyapunov stability theory, sufficient conditions are given to ensure the exponentially ultimate boundedness in the mean square of error dynamics system. Then, by combining with the linear matrix inequalities（LMIs） technology, the design method of estimator parameter is given. Finally, a numerical example is provided to testify the validity of the proposed state estimation approach.

关键词： Discrete delayed neural networks state estimation false data injection attacks WTOD protocol exponentially ultimate boundedness in the mean square

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A Deep Reinforcement Learning Method with Action Switching for Autonomous Navigation

A Deep Reinforcement Learning Method with Action Switching f...

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第40届中国控制会议

作者： Zuowei Wang Xiaozhong Liao Fengdi Zhang Min Xu Yanmin Liu Xiangdong Liu Xi Zhang Rui wei Dong Zhen Li School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing Aerospace Automatic Control Institute National Key Laboratory of Science and Technology on Aerospace Intelligence Control Capital Aerospace Machinery Co. Ltd.

Stochastic policy-based deep reinforcement learning（DRL） has successfully gained the widespread application but demands plenty of stochastic exploration to learn the environment at the initial training *** the agent is exposed to more complex environment,not only is the methodology inefficient,but its performance may also suffer from the issue of high *** paper develops a framework to accelerate the training procedure and reduce the variance by introducing a stochastic switching network,which specifically allows the agent to choose between heuristic actions and actions output by proximal policy optimization（PPO） *** of starting from the random actions,the agent can be effectively guided by the heuristic actions so that the navigation capability of the agent can be rapidly *** vanilla policy gradient（VPG） algorithm is further utilized to train the switching network,which can be jointly trained with the baseline *** the experimental comparison with the baseline PPO in the customized maze environment with openAI Gym toolkit,our method greatly contributes to the more efficient execution of navigation task by means of the heuristic actions for guidance.

关键词： Robot navigation proximal policy optimization（PPO） deep reinforcement learning（DRL） Vanilla policy gradient（VPG） action switching

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SPP-CNN: An Efficient Framework for Network Robustness Prediction

arXiv

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arXiv 2023年

作者： Wu, Chengpei Lou, Yang Wang, Lin Li, Junli Li, Xiang Chen, Guanrong The College of Computer Science Sichuan Normal University Chengdu610066 China The Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China The Department of Computer Science National Yang Ming Chiao Tung University Hsinchu300 Taiwan The Department of Automation Shanghai Jiao Tong University Shanghai200240 China The Institute of Complex Networks and Intelligent Systems Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai201210 China The Department of Control Science and Engineering Tongji University Shanghai200240 China The Department of Electrical Engineering City University of Hong Kong Hong Kong

This paper addresses the robustness of a network to sustain its connectivity and controllability against malicious attacks. This kind of network robustness is typically measured by the time-consuming attack simulation, which returns a sequence of values that record the remaining connectivity and controllability after a sequence of node- or edge-removal attacks. For improvement, this paper develops an efficient framework for network robustness prediction, the spatial pyramid pooling convolutional neural network (SPP-CNN). The new framework installs a spatial pyramid pooling layer between the convolutional and fully-connected layers, overcoming the common mismatch issue in the CNN-based prediction approaches and extending its generalizability. Extensive experiments are carried out by comparing SPP-CNN with three state-of-the-art robustness predictors, namely a CNN-based and two graph neural networks-based frameworks. Synthetic and real-world networks, both directed and undirected, are investigated. Experimental results demonstrate that the proposed SPP-CNN achieves better prediction performances and better generalizability to unknown datasets, with significantly lower time-consumption, than its counterparts. © 2023, CC BY.

关键词： complex networks

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Accurate Identification and Localization of Transmission Lines Under complex Lighting for Distribution Network Power Supply Operation Robots

Accurate Identification and Localization of Transmission Lin...

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Chinese Automation Congress (CAC)

作者： Tianhe Liu Xin Chen Chenyu Hu Xu Jian Shengzu Li Gang Wang 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 Equipment Technology Center State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Wuhan China Distribution Department State Grid Hubei Electric Power Co. Ltd. Wuhan Power Supply Company China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Accurate identification and position of transmission lines is critical for robots to safely and effectively perform distribution network operations. However, such tasks are often challenged by complex lighting conditions, where depth information can be easily lost. Transmission lines have limited texture features and reflective surfaces, making it difficult to match image feature points. To address these challenges, this paper proposes a visual perception system for weak texture targets under complex lighting, based on an “eye-on-hand” configuration and a depth complementation algorithm. Furthermore, a high-precision identification and localization method for transmission line grasping points is developed, utilizing the fusion of binocular visual color maps and depth maps. The proposed method has been shown to effectively solve the problem of identifying and localizing the grasping points of transmission lines under complex lighting conditions. Experiments demonstrated that the method can improve the localization accuracy to within $\pm 4\text{mm}$ , outperforming other algorithms. The method is characterized as simple and efficient, and it enhances the environmental adaptability of distribution network robots.

关键词： Location awareness Visualization Power transmission lines Accuracy Image color analysis Lighting Distribution networks Grasping Wire Robots

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Suppressing Stick-Slip Vibration of Drill-String System Subject to Actuator Saturation

Suppressing Stick-Slip Vibration of Drill-String System Subj...

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第40届中国控制会议

作者： Zhaoqing He Chengda Lu Min Wu Jun Gao 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 CCTEG Xi'an Research Institute

In this paper, the actuator saturation of drill-rig is considered in the mitigation of stick-slip vibration of the drill-string system. Firstly, the dynamic of stick-slip vibration is described by the combination of a multi-degree-of-freedom drill-string model and a bit-rock interaction model. To suppress stick-slip vibration while reducing the effect of saturation on control performance, a dynamic output feedback controller with an anti-windup compensator is introduced. Then, stability analysis of the resulting closed-loop system is carried out. By solving an optimization problem, the gain matrix of the anti-windup compensator is obtained. Finally, a case study is used to show the effectiveness of the method.

关键词： Drill-string system actuator saturation stick-slip vibration anti-windup compensator

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