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Hellinger distance based probability distribution approach to performance monitoring of nonlinear control systems

Chinese Journal of chemical Engineering 2015年第12期23卷 1945-1950页

作者：李晨黄彪钱锋 Key Laboratory of Advanced Control and Optimization Ministry of EducationEast China University of Science and Technology Department of Chemical and Materials Engineering University of Alberta

control performance monitoring has attracted great attention in both academia and industry over the past two decades. However, most research efforts have been devoted to the performance monitoring of linear control systems, without considering the pervasive nonlinearities(e.g. valve stiction) present in most industrial control systems. In this work, a novel probability distribution distance based index is proposed to monitor the performance of non-linear control systems. The proposed method uses Hellinger distance to evaluate change of control system performance. Several simulation examples are given to illustrate the effectiveness of the proposed method.

关键词： control performance monitoring Kernel density estimation Hellinger distance Nonlinear system

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Synchronization of multilayer networks with stochastic 11

Synchronization of multilayer networks with stochastic

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2017 11th Asian control Conference, ASCC 2017

作者： He, Wangli Lv, Siqi Peng, Chen Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 China School of Mechatronic Engineering and Automation Shanghai University 200072 China

ISBN: (纸本)9781509015733

This paper is concerned with synchronization in a network with two different types of interactions, formulated by multilayer networks. A switching law between the two layers is proposed, which follows a Bernoulli distribution. An appropriate mathematical model is constructed firstly to describe multilayer networks with stochastic switching layers. Then a mean square synchronization criterion is derived, which is followed by an alternative sufficient condition. Comparisons with the existing work are also included. Finally, an example is given to verify the theoretical results. © 2017 IEEE.

关键词： Synchronization

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Distributed Self-triggered control for Consensus of Multi-agent Systems

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IEEE/CAA Journal of Automatica Sinica 2014年第1期1卷 40-45页

作者： Hao Zhang Gang Feng Huaicheng Yan Qijun Chen the Department of Control Science and Engineering Tongji University the Department of Mechanical and Biomedical Engineering City University of Hong Kong Department of Mechanical and Biomedical Engineering City University of Hong Kong the Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education School of Information Science and Engineering East China University of Science and Technology Department of Control Science and Engineering Tongji University

This paper studies the consensus problem of general linear multi-agent systems via self-triggered control. Two distributed self-triggered control schemes based on state feedback and output feedback are developed respectively. It is shown that under the proposed control protocols, consensus can be reached if the communication graph of the multi-agent system is *** example is presented to illustrate the effectiveness of the proposed control methods.

关键词： Multi-agent system (MAS) consensus self-triggered control state feedback output feedback

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An application of the improved hybrid particle swarm optimization method in the gasoline blending process

An application of the improved hybrid particle swarm optimiz...

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International Workshop on advanced Computational Intelligence and Intelligent Informatics, IWACIII 2011

作者： Shu, Yue Cheng, Hui Liu, Yi Qi, Rongbin Liu, Zhao Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China SinoPec Jinling Petrochemical Ltd. Nanjing 210033 China

In this paper, an improved hybrid particle swarm optimization (IHPSO) method, which is able to handle the equality constraints efficiently, has been proposed to determine the optimal recipe offline for the gasoline blending process. In addition, the proposed method has been applied onsite in a gasoline production line in Nanjing, China. The results show that the optimized recipes are able to improve the first-time success rate for the blending process and decrease the quality giveaways and blending cost significantly.

关键词： Genetic algorithms

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Neural-observer-based adaptive control for stochastic nonlinear time-delay systems with unknown control directions 34

Neural-observer-based adaptive control for stochastic nonlin...

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34th Chinese control Conference, CCC 2015

作者： Zhaoxu, Yu Shugang, Li Fangfei, Li Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology Shanghai China Department of Industrial Engineering and Logistics Shanghai Jiao Tong University Shanghai China Department of Mathematics East China University of Science and Technology Shanghai China

ISBN: (纸本)9789881563897

The problem of output feedback adaptive stabilization is addressed for a class of stochastic nonlinear systems with unknown time-varying delays and unknown control directions in this paper. Firstly, the unknown control coefficients are lumped together by using a linear state transformation, and the original system is transformed into a new system for which control design becomes feasible. Then, after the design of a novel neural observer, an output feedback adaptive neural network (NN) controller is developed for such systems by combining the Dynamic Surface control (DSC) technique, the Nussbaum gain function (NGF) method and the Lyapunov-Krasovskii method. The proposed controller ensures that all signals in the closed-loop systems are bounded in probability. Finally, a simulation example is given to verify the effectiveness and applicability of the proposed control design. © 2015 Technical Committee on control Theory, Chinese Association of Automation.

关键词： neural network (NN) output feedback Stochastic systems time-varying delay unknown control direction

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Stability analysis and stabilization of semi-Markov jump linear systems with unavailable sojourn-time information

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Science China(Information Sciences) 2024年第7期67卷 211-223页

作者： Xiaotai WU Yang TANG Shuai MAO Ying ZHAO School of Mathematics and Physics Anhui Polytechnic University Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and Technology

This study addresses the stability and stabilization problems of discrete-time semi-Markov jump linear systems(S-MJLSs) with unavailable sojourn-time information. The sojourn-time probability mass functions(S-TPMFs) of discrete-time semi-Markov chains are no longer confined to the geometric distribution, and it is difficult to obtain accurate and comprehensive information for S-TPMFs in practice. This is because S-TPMFs are usually deduced from the statistical characteristics according to the sampled-data, while adequate samples are often costly and time consuming. In this study, when the S-TPMFs for semi-Markov chains are assumed to be unavailable, the σ-error mean square stability is investigated for discrete-time S-MJLSs with some widely used assumptions; for semi-Markov chains, only the transition probability matrix of the embedded chain is used. In addition, the existence conditions of the effective controller are provided for closed-loop systems without using the information of S-TPMFs. Numerical examples are presented to illustrate the validity of the obtained theoretical results.

关键词： semi-Markov chain semi-Markov jump linear systems σ-error mean square stability unavailable sojourn-time information

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Causal reasoning in typical computer vision tasks

arXiv

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arXiv 2023年

作者： Zhang, Kexuan Sun, Qiyu Zhao, Chaoqiang Tang, Yang Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China

Deep learning has revolutionized the field of artificial intelligence. Based on the statistical correlations uncovered by deep learning-based methods, computer vision has contributed to tremendous growth in areas like autonomous driving and robotics. Despite being the basis of deep learning, such correlation is not stable and is susceptible to uncontrolled factors. In the absence of the guidance of prior knowledge, statistical correlations can easily turn into spurious correlations and cause confounders. As a result, researchers are now trying to enhance deep learning methods with causal theory. Causal theory models the intrinsic causal structure unaffected by data bias and is effective in avoiding spurious correlations. This paper aims to comprehensively review the existing causal methods in typical vision and vision-language tasks such as semantic segmentation, object detection, and image captioning. The advantages of causality and the approaches for building causal paradigms will be summarized. Future roadmaps are also proposed, including facilitating the development of causal theory and its application in other complex scenes and systems. Copyright © 2023, The Authors. All rights reserved.

关键词： Object detection

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Input-Output Finite-Time Stability and Stabilization of Stochastic Fuzzy Systems With Randomly Occurring Uncertainties and Gain Fluctuations

Input-Output Finite-Time Stability and Stabilization of Stoc...

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World Congress on Intelligent control and Automation

作者： Jun Song Yugang Niu Yuanyuan Zou Key Laboratory of Advanced Control and Optimization for Chemical Process (East China University of Science and Technology) Ministry of Education Shanghai 200237 China

ISBN: (纸本)9781467384155

This paper studies the input-output finite-time stabilization problem of a class of fuzzy stochastic systems with randomly occurring uncertainties and (x, u)-dependent noises. By considering the randomly occurring gain fluctuations in controller gains, a fuzzy controller is designed to render the closed-loop system input-output finite-time stochastic stability with respect to some specified parameters. Through intensive stochastic analysis, a sufficient condition is established for the controller design via a convex optimization approach. A numerical example is exploited to demonstrate the effectiveness of the proposed design method.

关键词： Fuzzy systems Asymptotic stability Stability analysis Numerical stability Uncertainty Stochastic processes Aerospace electronics

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process Monitoring of Multimode processes Using Kernel Independent Component Analysis

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IFAC Proceedings Volumes 2012年第15期45卷 697-701页

作者： Yingwei Zhang Jiayu An Chi Ma State Key Laboratory of Synthetical Automation of Process Industry Northeastern University Shenyang Liaoning 110819 PR China Key Laboratory of Advanced Control and Optimization for Chemical Processes Shanghai 200237 PR China

In the paper, a new process monitoring approach is proposed for handling the multimode problem in the industrial processes. The original space can be separated into two different parts, which are the common part and the specific part. There are both similarity and dissimilarity in the underlying correlations of different modes, which play different roles in the industrial processes. Because the industrial processes have the non-Gaussian and nonlinear characteristics, modified kernel independent component analysis is used to monitor the multimode processes in this paper. The global multimode basis vector and the multimode sub-basis vector are obtained based on the modified KICA. Then, the common part and specific part in one mode are respectively analyzed. The proposed method is applied to monitor the continuous annealing process. The proposed approach effectively captures the non-Gaussian and nonlinear relationship in different modes in the industrial processes.

关键词： Multimode process monitoring Common and specific correlations Kernel independent component analysis

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Effect of effluent organic matter on ozonation of bezafibrate

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Frontiers of Environmental Science & Engineering 2015年第6期9卷 962-969页

作者： Huan HE Qian SUI Shuguang LU Wentao ZHAO Zhaofu QIU Gang YU State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process School of Resources and Environmental Engineering East China University of Science and Technology Shanghai 200237 China State Key Laboratory of Pollution Control and Resource Reuse College of Environmental Science and Engineering Tongji University Shanghai 200092 China School of Environment THU - VEOLIA Joint Research Center for Advanced Environmental Technology Tsinghua University Beijing 100084 China

The influence of three effluent organic matter （EfOM） model compounds, humic acid （HA）, bovine serum albumin （BSA）, and sodium alginate （AGS）, on the ozonation ofbezafibrate （BF）, a typical pharmaceutical and personal care product （PPCP）, was investigated. The results show that ozonation efficiently removed BF from aqueous solution with removal efficiencies 〉 95% within 8 min for all conditions. The reaction rate of BF decreased with increasing model compounds concentrations and the influence was more pronounced for HA and BSA, while less pronounced for AGS. Although BF concentration was significantly reduced, the degree of mineralization achieved was only approximately 11%. The addition of HA and BSA improved the mineralization of the solution, while the influence of AGS was minor. The acute toxicity of BF solution during ozonation was determined using the Luminescent bacteria test, and the toxicity exhibited an initial increase and a successive reduction. An overall decreased acute toxicity was observed with an increase of HA. The presence of BSA increased the formation rate of toxicity intermediates and resulted in inhibition peak forward.

关键词： ozonation bezafibrate acute toxicity humicacid bovine serum albumin sodium alginate

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