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Iterative Learning control for Distributed Parameter Systems Based on Non-Collocated Sensors and Actuators

IEEE/CAA Journal of Automatica Sinica 2020年第3期7卷 865-871页

作者： Jianxiang Zhang Baotong Cui Xisheng Dai Zhengxian Jiang Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) School of Internet of Things EngineeringJiangnan UniversityWuxi 214122China School of Electrical and Information Engineering Guangxi University of Science and TechnologyLiuzhou 545006China School of Science Jiangnan UniversityWuxi 214122China

In this paper, an open-loop PD-type iterative learning control(ILC) scheme is first proposed for two kinds of distributed parameter systems(DPSs) which are described by parabolic partial differential equations using non-collocated sensors and actuators. Then, a closed-loop PD-type ILC algorithm is extended to a class of distributed parameter systems with a non-collocated single sensor and m actuators when the initial states of the system exist some errors. Under some given assumptions, the convergence conditions of output errors for the systems can be obtained. Finally, one numerical example for a distributed parameter system with a single sensor and two actuators is presented to illustrate the effectiveness of the proposed ILC schemes.

关键词： Actuators distributed parameter system iterative learning control PD-type ILC scheme sensors

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Design of a visual information-based brain-computer interface control system

Design of a visual information-based brain-computer interfac...

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International Conference on Natural Computation (ICNC)

作者： Huiping Hu Jing Jin Yu Zhang Xingyu Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Shanghai China

ISBN: (纸本)9781467376808

Brain computer interface (BCI) could help patients to manipulate external devices based on the specific brain activities. One of the most popular BCI systems is the visual-based BCI system. Mostly, users were asked to pay attention not only to the target stimulus, but also to the real control target which would bring high workload to users and affect the control efficiency of BCI systems. In this paper, a real-time monitoring system was developed to solve this problem by showing the environment information from the camera on the computer screen. Five subjects took part in this experiment and all of them were asked to control a small car to the target position. Our result showed that all subjects could finish the task within two or three minutes. In this study, subject did not need to switch their attention on the car which was out of their sight, and it would help to improve the usability of BCI in the practical application.

关键词： Electrodes Silicon Biology Monitoring Electroencephalography Navigation Robots

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Optimal control nodes selection for consensus in multi-agent systems 19

Optimal control nodes selection for consensus in multi-agent...

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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Yang, Wen Wang, Xiaofan Shi, Hongbo Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 China Department of Automation Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9783902823625

In a resource limited multi-agent system, it is of practical importance to select a fraction of nodes (agents) to provide control inputs such that consensus can be achieved with optimized performance in terms of network cost and/or convergence speed. In this paper, we investigate the problem of how to select control nodes so as to minimize the network cost, where the control nodes are selected at the beginning and will be fixed all the time. This problem can be transformed to a combinatorial optimization problem, and further relaxed to a convex optimization problem with reweighted l1 norm. We propose a suboptimal algorithm to solve the convex optimization problem. Finally, we offer several numerical examples to illustrate the efficiency of the proposed strategies, and investigate the relationship how the degrees of control nodes will influence network cost and convergence speed. © IFAC.

关键词： Multi agent systems

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Data-driven Scheduling optimization of Ethylene Cracking Furnace System

Data-driven Scheduling Optimization of Ethylene Cracking Fur...

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Chinese control and Decision Conference, CCDC

作者： Xinwei Lin Liang Zhao Wenli Du Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai China

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

The ethylene cracking furnace system convert a variety of hydrocarbon feeds into products such as ethylene and propylene in parallel. During the cracking process, the coke produced by the cracking will degrade the performance of the cracking furnace, so the furnace should be cleaned periodically. Scheduling of the cracking furnace system involves various raw materials, multiple furnaces, and multiple constraints, so it is a difficult mathematic programming problem. Previous studies have simplified the optimization model to obtain a corresponding mixed integer nonlinear programming (MINLP) model. In order to make the scheduling more suitable for the actual process, this paper develops the transfer-line exchanger (TLE) model, fuel consumption model, and super-high pressure steam (SS) model by using the actual plant data. A case study is put forward to demonstrate the effectiveness of the proposed method.

关键词： Furnaces Feeds Mathematical model Job shop scheduling Raw materials optimization Fuels

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Just-in-time learning for cement free lime prediction with empirical mode decomposition and database monitoring index*

Just-in-time learning for cement free lime prediction with e...

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Asian control Conference

作者： Jinquan Zheng Wenli Du Weimin Zhong Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai China

ISBN: (纸本)9781728102634

Free lime (f-Cao) content is the key quality indicator in the control and optimization of cement calcination process. However, the cement process has many complex characteristics including large noise, time delay, nonlinearity, and time-varying system. To cope with the above characteristics, this study proposes just-in-time (JIT) learning with empirical mode decomposition (EMD) and database monitoring index (DMI) for free lime prediction. At first, EMD and Savitzky-Golay (S-G) filter can effectively deal with process large noise. Meanwhile, weighted time series analysis and mutual information are used to estimate large time delay. Then, least squares support vector machine (LSSVM) based on JIT and DMI is employed to solve the problems of process nonlinearity and time variation. The proposed strategy is validated on practical data from a cement plant.

关键词： Calcination Kilns Delay effects Mutual information Monitoring Indexes

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Gas Leakage Segmentation in Industrial Plants

Gas Leakage Segmentation in Industrial Plants

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Chinese Automation Congress (CAC)

作者： Haoqi Lin Xiaojing Gu Jingyu Hu Xingsheng Gu Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

Industrial gas leakage in chemical plants presents a high risk to health and safety, also makes a huge waste of production materials. In this paper, we propose an automatic gas segmentation method for optical gas imaging (OGI) videos, which can not only indicate the existence of leakage in frames but also show the precise locations and shapes of gas plumes. Specifically, we propose a novel video segmentation network that stacks 2D spatial convolutions, 1D temporal convolutions and 3D spatial-temporal convolutions together within an encoder-decoder structure, termed 2.5D-Unet. Stacking mixed convolutions increases the representation ability of network for leakage's appearance and motion. More importantly, stacking mixed convolutions facilitates pre-training of model using still images of smoke, which is especially useful when lacking of labeled videos of leaked gas. Experimental results show, for OGI video-based gas leakage segmentation, our method outperforms existing video segmentation methods.

关键词： Videos Feature extraction Image segmentation chemicals Data mining Three-dimensional displays Task analysis

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An Auto-tuning method for aeration control in activated sludge wastewater treatment processes

An Auto-tuning method for aeration control in activated slud...

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2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2022

作者： Nascu, Ioana Du, Wenli Nascu, Ioan Technical University of Cluj Napoca Automation Department Cluj-Napoca Romania Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Shanghai China Ministry of Education East China University of Science and Technology Key Laboratory of Advanced Control and Optimization for Chemical Processes Shanghai China Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai China

ISBN: (数字)9781665470957

ISBN: (纸本)9781665470957

In this paper, a relay-feedback PID auto-tuning method and applications related to conventional Wastewater Treatment Plants are presented. The developed method has two steps: identification of the process model parameters and PID controller tuning. First, to identify two points on the process Nyquist curve, a relay-feedback based experiment is proposed. A linear model of second order is obtained and this model is further used for the tuning of the PID controller. The performances of the control algorithms are illustrated by simulation results. Both the reference tracking and the disturbance rejection capability have been tested and analyzed. The impact of changing a design parameter in the closed loop system behavior has also been explored. © 2022 IEEE.

关键词： Wastewater treatment

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Gaussian process assisted coevolutionary estimation of distribution algorithm for computationally expensive problems

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Journal of Central South University 2012年第2期19卷 443-452页

作者： Luo, Na Qian, Feng Zhao, Liang Zhong, Wei-min Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai China

In order to reduce the computation of complex problems, a new surrogate-assisted estimation of distribution algorithm with Gaussian process was proposed. Coevolution was used in dual populations which evolved in parallel. The search space was projected into multiple subspaces and searched by sub-populations. Also, the whole space was exploited by the other population which exchanges information with the sub-populations. In order to make the evolutionary course efficient, multivariate Gaussian model and Gaussian mixture model were used in both populations separately to estimate the distribution of individuals and reproduce new generations. For the surrogate model, Gaussian process was combined with the algorithm which predicted variance of the predictions. The results on six benchmark functions show that the new algorithm performs better than other surrogate-model based algorithms and the computation complexity is only 10% of the original estimation of distribution algorithm.

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Intelligent droplet tracking with correlation filters for digital microfluidics

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Chinese chemical Letters 2021年第11期32卷 3416-3420页

作者： Libin Li Zhen Gu Jia-Le Zhou Bingyong Yan Cong Kong Hua Wang Hui-Feng Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and TechnologyShanghai 200237China Key Laboratory of East China Sea Fishery Resources Exploitation Ministry of Agriculture and Rural AffairsEast China Sea Fisheries Research InstituteChinese Academy of Fishery SciencesShanghai 200090China Department of Laboratory Medicine Renji HospitalSchool of MedicineShanghai Jiao Tong UniversityShanghai 200137China

Tracking the movement of droplets in digital microfluidics is essential to improve its control stability and obtain dynamic information for its applications such as point-of-care testing,environment monitoring and chemical ***,an intelligent,accurate and fast droplet tracking method based on machine vision is developed for applications of digital *** continuously recognize the transparent droplets in real-time and avoid the interferes from background patterns or inhomogeneous illumination,we introduced the correlation filter tracker,enabling online learning of the multi-features of the droplets in Fourier *** show the proposed droplet tracking method could accurately locate the *** also demonstrated the capacity of the proposed method for estimation of the droplet velocity as faster as 20 mm/s,and its application in online monitoring the Griess reaction for both colorimetric assay of nitrite and study of reaction kinetics.

关键词： Digital microfluidics Correlation filter trackers Machine vision Reaction kinetics Colorimetric assay

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Quantum clustering-based weighted linear programming support vector regression for multivariable nonlinear problem

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Soft Computing 2009年第9期14卷 921-929页

作者： Yu, Yanfang Qian, Feng Liu, Huimin Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China

Linear programming support vector regression shows improved reliability and generates sparse solution, compared with standard support vector regression. We present the v-linear programming support vector regression approach based on quantum clustering and weighted strategy to solve the multivariable nonlinear regression problem. First, the method applied quantum clustering to variable selection, introduced inertia weight, and took prediction precision of v-linear programming support vector regression as evaluation criteria, which effectively removed redundancy feature attributes and also reduced prediction error and support vectors. Second, it proposed a new weighted strategy due to each data point having different influence on regression model and determined the weighted parameter p in terms of distribution of training error, which greatly improved the generalization approximate ability. Experimental results demonstrated that the proposed algorithm enabled the mean squared error of test sets of Boston housing, Bodyfat, Santa dataset to, respectively, decrease by 23.18, 78.52, and 41.39%, and also made support vectors degrade rapidly, relative to the original v-linear programming support vector regression method. In contrast with other methods exhibited in the relevant literatures, the present algorithm achieved better generalization performance.

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