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International Conference on Mechatronics and control (ICMC)

作者： Quan Wang Yuanyuan Zou Yugang Niu Key Laboratory of Advanced Control and Optimization for Chemical Processes East China Univ. of Science and Technology Shanghai China

ISBN: (纸本)9781479925391

In order to save communication consumption in the wireless nodes of networked control systems, this paper investigates the stabilization problem of an event-triggered constrained model predictive control. A state-feedback predictive control law is designed by solving an infinite horizon performance objective and an event-triggered condition involving the norm of a measurement error is derived based on input-to-state stability. Under the proposed mechanism, the measurements are sent by wireless network and the predictive control optimization is implemented only when the triggering conditions are satisfied. This approach not only can alleviate the energy consumption but also achieves the desired control performance and constraints satisfaction. Finally, an example is given to illustrate the effectiveness of the proposed results.

关键词： Predictive control Wireless sensor networks Networked control systems Closed loop systems Wireless networks

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Stability Analysis of Full Form Dynamic Linearization controller Based Data-driven Model Free Adaptive control

Stability Analysis of Full Form Dynamic Linearization Contro...

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第28届中国控制与决策会议

作者： Yuanming Zhu Shangtai Jin IEEE Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and Technology Advanced Control System Laboratory Beijing Jiaotong University

ISBN: (纸本)9781467397155

Full form dynamic linearization controller based data-driven model free adaptive control algorithm has been studied in control *** method merely requires the I/O data of the plant to design the controller and is easy for ***,there still lacks necessary research on the conditions which can guarantee the stability of the closed loop *** paper presents a stability analysis result for a class of nonlinear *** some mild assumptions,the convergence of the output regulating error was derived by rigorous mathematical method,which guarantees the correctness of the proposed method in theory.

关键词： Dynamic Linearization controller Data-driven Model Free Adaptive control Nonlinear System

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A Fast Global Group Search Optimizer algorithm

A Fast Global Group Search Optimizer algorithm

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International Conference on Information and Automation (ICIA)

作者： Kang Zhang Xingsheng Gu Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Ministry of Education Shanghai

The Group Search Optimizer(GSO) is a novel optimization algorithm, which is inspired by searching behavior of animals. In this paper, we proposed an improved GSO algorithm named Fast Global Group Search Optimizer(FGGSO) to increase searching speed and balance the exploitation and exploration of the algorithm, which is based on our previous works. At first time, considering the complexity and time-consuming design of the producer's angle searching strategy, a novel local search mechanism, named campaign strategy, is developed, which is inspired by competition and cooperation between candidates in an electoral process. After that, a reconstruction operation is applied in searching process to guarantee the avoidance of the local minimum. The algorithm is evaluated on a set of 11 numerical optimization problems and compared favorably with other version of GSOs. Experimental results indicate the remarkable improvement on the performance of these problems.

关键词： optimization Standards Animals Acceleration Biological system modeling Convergence Search problems

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processing modelling development through artificial neural networks and hybrid models

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Computers & chemical Engineering 2000年第2期24卷 1355-1360页

作者： L.F.M. Zorzetto R.Maciel Filho M.R. Wolf-Maciel Dupont-Brazil Campinas SP Brazil Laboratory of Optimization Design and Advanced Process Control (LOPCA) School of Chemical Engineering Campinas-SP CP: 6066 CEP 13081-970 Campinas Brazil

Developing fully mechanistic models for bioprocess is expensive and time-consuming. On the other hand, using pure ‘black-box’ approaches can lead to a misuse of available information, because there are aspects of the process that can be accurately described by simple equations as, for example, mass balances. This work analyses the use of different types of ‘black-box’ and hybrid models to outline the dynamics of a batch beer production. The hybrid models, combine mechanistic equations with ‘black-box’ techniques (reserved only for the unclear parts of the system), in order to achieve an efficient use of the available information. The hybrid models can also be called ‘grey-box’ approaches. To generate the hybrid models, different level of information is introduced into the ‘black-box’ models, allowing for an interesting model performance comparison in the end. Results demonstrate that the ‘black-box’ models present a good performance in the range of process conditions used to develop them. However, the inclusion of mechanistic knowledge into the hybrid models increase the model extrapolative capability. In this work, artificial neural networks (ANN) are used as the main technique for both the ‘black-box’ models and the ‘black-box’ parts in the hybrid models.

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Automatic ocular artifact suppression from human operator's EEG based on a combination of independent component analysis and fuzzy c-means clustering techniques

Automatic ocular artifact suppression from human operator's ...

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Chinese control Conference (CCC)

作者： Raofen Wang Jianhua Zhang Xingyu Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Shanghai 200237 China

Independent component analysis (ICA) and fuzzy c-means (FCM) clustering were adopted for automatic ocular artifact suppression from operator's electroencephalogram. Firstly, ICA was applied to the 20s data containing nine channels of EEG data and one of electrooculagram (EOG) data. Secondly, each 20s independent component (IC) was partitioned into ten 2 s epochs. And five features of each epoch were calculated, which are wavelet entropy, power in the band between 0 and 5 Hz, kurtosis, mutual information and correlation. Thirdly, the epochs were classified as either EEG or ocular artifact based on the result of FCM clustering. And then components which were recognized as ocular artifact were rejected. Clean EEG was obtained. The result shows that the method based on ICA and FCM can be applied to online automatic ocular artifact suppression from EEG.

关键词： Electroencephalography Electrooculography Independent component analysis Entropy Electronic mail optimization Laboratories

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Semi-Global Containment control of Linear Agents with Actuator Position and Rate Saturation: The State Feedback Case

Semi-Global Containment Control of Linear Agents with Actuat...

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Chinese control Conference (CCC)

作者： Zhiyun Zhao Hongbo Shi Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Shanghai P. R. China

This paper studies semi-global containment control problem for a multi-agent system. Each follower agent in the system is described by a general linear system in the presence of both actuator position and rate saturation. A linear state feedback containment control law is constructed for each follower agent by using low gain approach such that the states of all follower agents will converge to the convex hull formed by the leader agents asymptotically when the communication topology among follower agents is a connected undirect graph and each leader agent is a neighbor of at least one follower agent. Simulation results illustrate the theoretical results.

关键词： Actuators Multi-agent systems State feedback Linear systems Topology Output feedback Decentralized control

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

Hellinger distance based probability distribution approach t...

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作者： Li, Chen Huang, Biao Qian, Feng Key Laboratory of Advanced Control and Optimization Ministry of Education East China University of Science and Technology Shanghai200237 China Department of Chemical and Materials Engineering University of Alberta EdmontonABT6G 2G6 Canada

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. © 2015 The chemical Industry and Engineering Society of China, and chemical Industry Press. All rights reserved.

关键词： Probability distributions

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Multiple models robust adaptive control with reduced model

Multiple models robust adaptive control with reduced model

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

作者： Liu, Jiazhen Wang, Zhenlei Wang, Xin Wang, Dahai 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 Center of Electrical and Electronic Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781424451951

The traditional robust adaptive control broadens the application of the routine adaptive control because of considering the uncertainty of the practice plant. However, traditional robust adaptive control solves the problem that the plant would be unstable under some uncertainties and it often ignores the dynamic property and steady-state property, which makes the traditional robust adaptive control unfit for practice plant, whose working condition changes randomly. To solve these problems, this paper designs multiple models robust adaptive controller for the plant which can be describeled by Autoregressive Moving Average (ARMA) model and with unmodeled dynamics. First, the normalization factor is used to convert the system unmodeled dynamic to bounded disturbance, and then, many fixed controller and two robust adaptive controllers are designed based on system reduced model according to the changing range of the working condition and the best controller computed by the performance index is chosen as the working controller. Simulation illustrates that the proposed method is preferable when there are unmodeled dynamics and changing working condition. © 2010 IEEE.

关键词： controllers

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Quantized and networked predictive control for input-saturated systems

Quantized and networked predictive control for input-saturat...

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作者： Zou, Yuanyuan Chen, Bei Jia, Tinggang Niu, Yugang Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China Central Academe Shanghai Electric Group Co. Ltd. Shanghai China

ISBN: (纸本)9789881725592

This paper investigates the problem of stabilizing predictive control for constrained systems with quantization and communication delays. Based on the quantization matrix, the input-saturated control systems with logarithmic quantizers are described as constrained control systems with structured norm-bounded uncertainties. A quantized and networked predictive control algorithm is presented by using a multirate delay compensation strategy. It is shown that the proposed predictive controller not only efficiently reduces the negative effects of the quantization and communication delays but also guarantees the closed-loop stability and constraints satisfaction. The simulation example shows the effectiveness of the derived method. © 2011 Chinese Assoc of Automati.

关键词： Networked control systems

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Dynamic simulation of primary esterification section of poly(ethylene-terephthalate)

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Huagong Xuebao/CIESC Journal 2010年第8期61卷 1933-1941页

作者： Luo, Na Ye, Zhencheng Zhong, Weimin Qian, Feng School of Information Science and Engineering East China University of Science and Technology Shanghai 200237 China Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Shanghai 200237 China

Dynamic model is the basis of dynamic optimization in chemical process. In this paper a dynamic model for esterification section of poly(ethylene-terephthalate) (PET) was developed using segment method. Different from other researches, the model considered the interaction between esterification reactor and the column. Dynamic responses of process operating condition were analyzed with basic control strategies. Simulation results show that properties of products such as carboxyl end concentration, degree of polymerization response quickly to step change of feed molar ratio, reactor temperature, pressure and liquid level. Also these step changes significantly affected the changes in gas flow of ethylene glycol and water. control system plays a significant role in the stability of PET esterification process. © All Rights Reserved.

关键词： Polyethylene terephthalates

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