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The 24th Chinese control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

作者： Wenyong Wang Ziqiang Sun Huanlai Cao Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education E Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education E

It is known that the characteristic of Dissolved Oxygen (DO) control system is non-linear, variability and uncertainty, etc. This paper presents Genetic Algorithm (GA) to optimize the fuzzy controller, which adjusts the membership function of fuzzy controller parameters by GA. The results show that the optimized fuzzy controller based on GA is well up for the shortage of the traditional fuzzy controller. With this controller we can get target such as: obtaining better control result, improving the efficiency of sewage treatment, having significant effect for stable and secure running and reducing energy consumption.

关键词： Sewage treatment Dissolved oxygen Fuzzy control Genetic algorithm

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A Comparison of Navigation System Based on P300 BCI and SSVEP BCI

A Comparison of Navigation System Based on P300 BCI and SSVE...

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The 24th Chinese control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

作者： Lijing Meng Jing Jin Xingyu Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationSc Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education S

A navigation system based on P300 brain computer interface system (BCIs) and steady-state visual evoked potentials (SSVEP) BCIs respectively was designed in this paper. In the experiment, subjects were required to move a ball on the computer screen to the target position by P300 BCI system and SSVEP BCI system. Bayesian linear discriminant analysis (BLDA) is used to detect P300 potentials and canonical correlation analysis (CCA) is used to detect SSVEP. The aim of this paper is to show the drawbacks and advantages of these two BCIs, when they were used in navigation task. The online experimental results show that P300 BCIs is more robust for subjects compared to SSVEP BCIs.

关键词： P300 Steady-State Visual Evoked Potentials (SSVEP) Brain Computer Interface Navigation System

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Multimode Process Monitoring Based on Fuzzy C-Means in Locality Preserving Projection Subspace

Multimode Process Monitoring Based on Fuzzy C-Means in Local...

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第23届过程控制会议

作者： Xiang Xie Hongbo Shi Key Laboratory of Advanced Control and Optimization for Chemical Processes(East China University of Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of

For complex industrial processes with multiple operating conditions, it is important to develop effective monitoring algorithms to ensure the safety of the producing processes. This paper proposes a novel monitoring strategy based on fuzzy c-means (FCM). First, the high dimensional historical data are transferred to a low dimensional subspace space by locality preserving projection (LPP). Then the scores in the novel subspace are classified into several overlapped clusters, each representing an operating mode. After that, the distance statistics of each cluster are integrated though the membership values into a novel BID monitoring index. The efficiency and effectiveness of the proposed method are validated though the Tennessee Eastman (TE) benchmark process.

关键词： Multimode process monitoring fuzzy c-means locality preserving projection integrated monitoring index Tennessee Eastman process.

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Sliding mode control for Markovian jump systems under deception attacks 33

Sliding mode control for Markovian jump systems under decept...

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第33届中国控制与决策会议

作者： Bei Chen Yugang Niu Zhiru Cao The School of Electric and Electronic Engineering Shanghai University of Engineering Science The Key Laboratory of Advanced Control and Optimization for Chemical Process (East China University of Science and Technology) Ministry of Education The Key Laboratory of Advanced Control and Optimization for Chemical Proces (East China University of Science and Technology)s Ministry of Education

ISBN: (纸本)9781665431293

This research article considers the design of static output-feedback sliding mode control for Markovian jump systems,in which the attacker may inject false information into the communication channel between the controller and the *** key issue is how to design the feasible sliding mode control law to overcome the effects of unknown and time-varying *** this end,an on-line estimation scheme is introduced to deal with the unknown network attack *** then,a linear sliding surface is constructed based on the measured output information and an outputfeedback sliding mode controller is correspondingly *** is shown that the reachability of the specified sliding surface can be achieved and the asymptotic stability of the closed-loop system can be ensured under the derived sufficient ***,simulation examples are provided to verify the developed static output-feedback sliding mode control strategy.

关键词： Markovian Jump Systems Sliding Mode control Deception Attacks Static Output-feedback control

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Feature extraction of vigilance level based on Heart Rate Variability of Electrocardiogram

Feature extraction of vigilance level based on Heart Rate Va...

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2011 4th International Conference on Biomedical Engineering and Informatics, BMEI 2011

作者： Yu, Shanshan Wang, Bei Wang, Yujue Wang, Xingyu Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Ministry of Education No. 130 Meilong St. Shanghai 200237 China

ISBN: (纸本)9781424493524

This paper presented a simple method of detecting the peak of R wave in Electrocardiogram (ECG) signal and computing the Heart Rate Variability (HRV). Features were extracted from the obtained HRV to analyze the vigilance level during day time short nap sleep. Firstly, the second derivative of ECG signal was calculated and clustered in order to detect the peak of R wave. Secondly, HRV was calculated from the subtraction of two adjoining R waves. Finally, several features were extracted based on HRV in time domain and frequency domain. The variation of vigilance level during the day time short nap was analyzed based on the extracted features. The result showed that the accuracy of peak detection of R wave in ECG signal was about 99.5%. The extracted features can reflect the changing of vigilance level and be useful for sleep stage analysis. © 2011 IEEE.

关键词： Electrocardiograms

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A novel deep quality-supervised regularized autoencoder model for quality-relevant fault detection

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Science China(Information Sciences) 2022年第5期65卷 280-282页

作者： Zhichao LI Li TIAN Xuefeng YAN Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

Dear editor,In the industrial processes, timely detection of key quality variables is very important for tracking the product quality, monitoring the process status, and achieving stable and reliable control. However,... 详细信息

关键词： supervised learning deep learning regularized autoencoder process monitoring quality-relevant fault detection

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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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Study on an improved bee colony algorithm and its application in optimization of PX oxidation process

Study on an improved bee colony algorithm and its applicatio...

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

作者： Li, Xinmao Xing, Jianliang Luo, Na Zhong, Weimin Cheng, Hui Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Shanghai China College of Chemical Engineering East China University of Science and Technology Shanghai China

For the deficiencies of the basic bee colony algorithm based on the mechanism of nectar (ABC), such as the population diversity scarcity in the early iterations and easily sticking into the local optimum, a strategy which integrates an improved differential evolution (DE) method into bee colony algorithm (DE-ABC) is proposed. The primary idea of DE-ABC is to introduce DE into the mutation of employed bee instead of random search strategy, and combination of incremental strategy of the crossover probability factor and the scaling factor, strategy of stagnation judgment and treatment. Four benchmark functions are used to make a comparison, and results show that DE-ABC converges with a faster accelerated rate and a higher accuracy optimization. Then DE-ABC is applied to the optimization of p-xylene oxidation process. With the purpose of reducing the exhaust CO, CO2 of the reactor and the first crystallizer, an excellent solution of the operating variables is obtained under the process operating parameters constraints, which gives a guide to the plant operation.

关键词： optimization

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Distributed predictive control for energy management of multi-microgrids systems

Distributed predictive control for energy management of mult...

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13th IFAC Symposium on Large Scale Complex Systems: Theory and Applications, LSS 2013

作者： Xu, Jun Zou, Yuanyuan Niu, Yugang Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China Univ. of Science and Technology Shanghai 200237 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai 200240 China

In this paper, a distributed model predictive control (DMPC) scheme is presented to optimize the power flow management of microgrids in smart grid environment. For a multi-microgrids system in which local microgrid links with each other through particular channels for power and information, the proposed method can maximize the overall energy efficiency. The DMPC optimization problem is formulated by minimizing the surplus/insufficient energy in each microgrid and a constraint restriction is imposed to guarantee the closed-loop stability. A simulation example is carried out to demonstrate the feasibility and effectiveness of this energy management strategy. © IFAC.

关键词： Electric power distribution

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A new particle swarm optimization and the application in the soft sensor modeling

A new particle swarm optimization and the application in the...

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2010 8th IEEE International Conference on control and Automation, ICCA 2010

作者： Dang, Mingmei Wang, Zhenlei Qian, Feng East China University of Science and Technology China Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China

ISBN: (纸本)9781424451951

Aiming at the disadvantages of the standard Particle Swarm optimization (PSO), a new particle swarm optimization algorithm based on dual mutation(DDPSO) is proposed. By comparing and analyzing the results of several Benchmark functions, the excellent performance of PSO is proved. The improved PSO is applied to optimize the structure and parameters in artificial neural network(ANN). The availability of algorithm optimizing neural network is proved by applying ANN in soft sensor modeling of propylene concentration measurement. © 2010 IEEE.

关键词： Neural networks

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