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第三十八届中国控制会议

作者： Changjiang Chen Fei Chen Department of Automation Xiamen University State Key Laboratory of Synthetical Automation for Process Industries Northeastern University School of Control Engineering Northeastern University at Qinhuangdao

We consider the distributed average tracking(DAT) problem for multiple time-varying signals subject to both process and measurement noise under a directed time-varying communication network. In order to attenuate the effect of the noise, we construct a Kalman filter for each agent, based on which we design a discrete-time consensus-based DAT algorithm. It is shown that the proposed algorithm can track the average of the reference signals with small steady-state error. A numerical example is presented to validate the theoretical results.

关键词： Distributed average tracking noise Kalman filter multi-agent system

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A simplified prediction-correction algorithm for time-varying convex optimization

A simplified prediction-correction algorithm for time-varyin...

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第三十八届中国控制会议

作者： Zhicong Lin Fei Chen Linying Xiang Ge Guo Department of Automation Xiamen University State Key Laboratory of Synthetical Automation for Process Industries Northeastern University School of Control Engineering Northeastern University at Qinhuangdao

This paper studies a time-varying unconstrained convex optimization problem under the prediction-correction *** primary objective is to devise a simplified prediction-correction algorithm, which can solve the time-varying unconstrained convex optimization problem effectively without the need to compute the inverse of the Hessian matrix of the cost *** this aim, we propose a simplified prediction step and provide the theoretical analysis on the convergence of the resulting algorithm. The results show that, under suitable conditions, the error bound of our algorithm is O（h）, which is at the same level as those reported in the literature. We demonstrate the validity of the proposed algorithm by a numerical example.

关键词： Convex optimization time-varying optimization simplified prediction-correction

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Online complex nonlinear industrial process operating optimality assessment using modified robust total kernel partial M-regression

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Chinese Journal of Chemical engineering 2018年第4期26卷 775-785页

作者： Fei Chu Wei Dai Jian Shen Xiaoping Ma Fuli Wang School of Information and Control Engineering China University of Mining and Technology Xuzhou 221116 China State Key Laboratory of Integrated Automation for Process Industries Northeastern University Shenyang 110819 China College of Information Science and Engineering Northeastern University Shenyang 110819 China

Although industrial processes often perform perfectly under design conditions, they may deviate from the optimal operating point owing to parameters drift, environmental disturbances, etc. Thus, it is necessary to develop efficacious strategies or procedure to assess the process performance online. In this paper, we explore the issue of operating optimality assessment for complex industrial processes based on performance-similarity considering nonlinearities and outliers simultaneously, and a general enforced online performance assessment framework is proposed. In the offline part, a new and modified total robust kernel projection to latent structures algorithm,T-KPRM, is proposed and used to evaluate the complex nonlinear industrial process, which can effectively extract the optimal-index-related process variation information from process data and establish assessment models for each performance grades overcoming the effects of outlier. In the online part, the online assessment results can be obtained by calculating the similarity between the online data from a sliding window and each of the performance grades. Furthermore, in order to improve the accuracy of online assessment, we propose an online assessment strategy taking account of the effects of noise and process uncertainties. The Euclidean distance between the sliding data window and the optimal evaluation level is employed to measure the contribution rates of variables, which indicate the possible reason for the non-optimal operating performance. The proposed framework is tested on a real industrial case: dense medium coal preparation process, and the results shows the efficiency of the proposed method comparing to the existing method.

关键词： Performance assessment Optimization Model Economics T-KPRM Robust

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Facial expression recognition based on deep residual network

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Journal of Computers (Taiwan) 2020年第2期31卷 12-19页

作者： Qu, Junsuo Zhang, Ruijun Zhang, Zhiwei Pan, Jeng-Shyang Xi'an Key Laboratory of Advanced Control and Intelligent Process School of Automation Xi'an University of Posts and Telecommunications Xi'an710061 China Innovation Lab Xi'an University of Posts and Telecommunications Xi'an710061 China School of Information Science and Engineering Fujian University of Technolgy Fuzhou350000 China

Low accuracy of facial expression recognition for traditional methods, a facial expression recognition algorithm is proposed. Using the deep residual network model as the feature extractor, the residual block of the residual network is improved to enhance the information flow in the deep network. During training, apply some pre-processing techniques to extract only expression specific features from a face image and explore the presentation order of the samples and use softmax to classify and identify the extracted feature vectors. The experimental results show that a higher recognition rate is obtained on FER-2013. © 2020 Computer Society of the Republic of China. All rights reserved.

关键词： Face recognition

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A Primal-Dual SGD Algorithm for Distributed Nonconvex Optimization

arXiv

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arXiv 2020年

作者： Yi, Xinlei Zhang, Shengjun Yang, Tao Chai, Tianyou Johansson, Karl H. The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden The Department of Electrical Engineering University of North Texas DentonTX76203 United States The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

The distributed nonconvex optimization problem of minimizing a global cost function formed by a sum of n local cost functions by using local information exchange is considered. This problem is an important component of many machine learning techniques with data parallelism, such as deep learning and federated learning. We propose a distributed primal–dual stochastic gradient descent (SGD) algorithm, suitable for arbitrarily connected communication networks and any smooth (possibly nonconvex) cost functions. We show that the proposed algorithm achieves the linear speedup convergence rate O(1/√nT) for general nonconvex cost functions and the linear speedup convergence rate O(1/(nT)) when the global cost function satisfies the Polyak–Lojasiewicz (P–L) condition, where T is the total number of iterations. We also show that the output of the proposed algorithm with constant parameters linearly converges to a neighborhood of a global optimum. We demonstrate through numerical experiments the efficiency of our algorithm in comparison with the baseline centralized SGD and recently proposed distributed SGD algorithms. Copyright © 2020, The Authors. All rights reserved.

关键词： Cost functions

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Oil-water two-phase flow velocity measurement with Continuous wave ultrasonic Doppler 22

Oil-water two-phase flow velocity measurement with Continuou...

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22nd World Congress of the International Measurement Confederation, IMEKO 2018

作者： Liu, Weiling Tan, Chao Dong, Feng Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering and Automation Tianjin University Tianjin300072 China

Oil-water two-phase flow exists widely in many industries. Accurate measurement of flow velocity is of significance for quantify the volume or mass flow rate as well as monitor the operation safety. A non-intrusive one-side Continuous Wave Ultrasonic Doppler (CWUD) sensor is presented for measuring the overall superficial velocity of oil-water two-phase flow. The one-side CWUD sensor consists of two-chip transducer with resonant frequency of 1MHz, both of which are installed at the bottom of test pipe, and the sample volume cover the whole radial direction of pipe cross-section. The Doppler shift signal collected by ultrasonic sensor is directly related to the average velocity of dispersed phase within the sample volume of CWUD. The overall superficial flow velocity is derived by a linear correction of measured average velocity, based on the analysis of average Doppler shift properties in different flow conditions, i.e. water continuous flow and oil continuous flow. Dynamic experiments were conducted at a horizontal oil-water two-phase flow loop. It can be found that the average Doppler shift within the sample volume increases with overall superficial flow velocity, however, varies with different continuous phases at the same overall superficial flow velocity. The results show that the mean relative error of overall superficial flow velocity is 3.45%. © 2018 Web Portal IOP. All rights reserved.

关键词： Flow velocity

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Dexterous Manipulation through Imitation Learning: A Survey

arXiv

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arXiv 2025年

作者： An, Shan Meng, Ziyu Tang, Chao Zhou, Yuning Liu, Tengyu Ding, Fangqiang Zhang, Shufang Mu, Yao Song, Ran Zhang, Wei Hou, Zeng-Guang Zhang, Hong School of Electrical and Information Engineering Tianjin University Tianjin300072 China School of Control Science and Engineering Shandong University Jinan250061 China State Key Laboratory of General Artificial Intelligence Beijing100086 China Department of Mechanical and Process Engineering ETH Zurich Zurich8092 Switzerland Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen518055 China School of Informatics University of Edinburgh EH8 9AB United Kingdom Department of Computer Science University of Hong Kong 999077 Hong Kong State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China CASIA-MUST Joint Laboratory of Intelligence Science and Technology Institute of Systems Engineering Macau University of Science and Technology 999078 China

Dexterous manipulation, which refers to the ability of a robotic hand or multi-fingered end-effector to skillfully control, reorient, and manipulate objects through precise, coordinated finger movements and adaptive force modulation, enables complex interactions similar to human hand dexterity. With recent advances in robotics and machine learning, there is a growing demand for these systems to operate in complex and unstructured environments. Traditional model-based approaches struggle to generalize across tasks and object variations due to the high-dimensionality and complex contact dynamics of dexterous manipulation. Although model-free methods such as reinforcement learning (RL) show promise, they require extensive training, large-scale interaction data, and carefully designed rewards for stability and effectiveness. Imitation learning (IL) offers an alternative by allowing robots to acquire dexterous manipulation skills directly from expert demonstrations, capturing fine-grained coordination and contact dynamics while bypassing the need for explicit modeling and large-scale trial-and-error. This survey provides an overview of dexterous manipulation methods based on imitation learning (IL), details recent advances, and addresses key challenges in the field. Additionally, it explores potential research directions to enhance IL-driven dexterous manipulation. Our goal is to offer researchers and practitioners a comprehensive introduction to this rapidly evolving domain. Copyright © 2025, The Authors. All rights reserved.

关键词： Grippers

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Dead-Time Compensator for State-delay Stable Systems

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IFAC-PapersOnLine 2018年第18期51卷 672-677页

作者： Albertos, P. García, P. Chen, Q. Luan, X. Department of Systems Engineering Control Instituto de Automática e Informática Industrial Universitat Politècnica deValència Spain Key Laboratory of Advance Process Control for Light Industries Institute of Automation Jiangnan University China

This paper deals with the control of simple process models with state-delays. A pre-compensator is used to cancel the delay. Due to the cancellation of some terms, the process as well as its undelayed part should be stable. Although the approach is general, in order to simplify the notation, second order systems are considered to describe the procedure. The proposed methodology is applied to compensate the delay in a recycled reactor as well as to control a pure state-delayed academic example. © 2018

关键词： process control Delay control systems Recycling control design Dead time compensator Dead time compensation Pre compensator Second order systemss Stable systems State delay Time delay systems

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Retraction Note: Evaluation on diabetic plantar pressure data-set employing auto-segmentation technologies

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Neural Computing and Applications 2024年第24期36卷 15219-15219页

作者： Chen, Hongwei Cao, Luying Li, Zairan Hemanth, D. Jude Wu, Lijun de Albuquerque, Victor Hugo C. Shi, Fuqian Department of Orthopedics Yiwu Central Hospital Wenzhou Medical University Wenzhou People’s Republic of China Institute of Digitized Medicine Wenzhou Medical University Wenzhou People’s Republic of China Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering and Automation Tianjin University Tianjin People’s Republic of China Department of ECE Karunya University Coimbatore India Programa de Pós-Graduação Em Informática Aplicada Universidade de Fortaleza Fortaleza Brazil

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Preface——Special Issue on New Directions in Nonlinear and Distributed control

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Journal of Systems Science & Complexity 2018年第1期31卷 1-3页

作者： LIU Tengfei XIN Bin JIANG Zhong-Ping State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang 110819 China School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing 100081 China Tandon School of Engineering New York University Brooklyn NY 11201 USA

Nonlinearity is ubiquitous in engineering and natural *** development of nonlinear control can be traced back to decades *** date,the research has reached the stage that emphasizes developing methodologies that can ha... 详细信息

关键词：控制问题非线性分布式工程应用程序电子物理自然系统生产线相互作用

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