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第三十三届中国控制会议

作者： LOU Xuyang YE Qian CUI Baotong Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Jiangnan University School of IoT Engineering Jiangnan University Wuxi Institute of Technology

ISBN: (纸本)9781479947249

By ordinary Takagi-Sugeno(TS) fuzzy models, complex nonlinear systems can be represented to a set of linear submodels by using fuzzy sets and fuzzy reasoning. This paper is concerned with the problem of observer-based state estimation for fuzzy neural networks(FNNs) with time-varying structured uncertainties and time-varying delay. The problem addressed is to estimate the neuron states, through available output measurements, such that the dynamics of the estimation error is globally exponentially stable. An effective linear matrix inequality approach is developed to solve the neuron state estimation *** particular, we derive the conditions for the existence of the desired estimators of the delayed neural networks for all admissible parametric uncertainties. The designed controller simultaneously contains both the current state information and nonlinear disturbances on the network outputs and can be derived by solving a linear matrix inequality(LMI). A numerical example is included to illustrate the applicability of the proposed design method.

关键词： State Estimation,Fuzzy Neural Networks,Observer,Delay

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Automatic Sleep Stage Classification for Daytime Nap Based on Hopfield Neural Network

Automatic Sleep Stage Classification for Daytime Nap Based o...

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第25届中国控制与决策会议

作者： Xi Chen Bei Wang Xingyu Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology) Ministry of Education School of Information Science and Engineering East China University of Science and Technology

ISBN: (纸本)9781467355339

In this study, automatic method of sleep stage classification for daytime nap is investigated. The ultimate objective is to identify the changing of sleep level during one's nap. The sleep data is recorded according to the polysomnographic (PSG) measurement. The Electroencephalograph (EEG) is analyzed for sleep stage classification. Totally, 4 parameters are selected and calculated for each 20-second segment of EEG data. The main method is based on Hopfield Neural Network (HNN). The neural network is trained by using standard mode. The sleep stages are classified based on HNN for each consecutive segment. The obtained result showed about 80.6% consistence comparing with the visual inspection. The automatic classification results indicated the changing of sleep level during nap, which can be useful for daytime nap sleep evaluation.

关键词： Sleep Stage Determination, Daytime Nap, EEG, Hopfield Neural Network

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Templated spherical coassembly strategy to fabricate MoS2/C hollow spheres with physical/chemical polysulfides trapping for lithium-sulfur batteries

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Journal of Materials Science & Technology 2022年第03期98卷 136-142页

作者： Ting He Jiajia Ru Yutong Feng Dapeng Bi Jiansheng Zhang Feng Gu Chi Zhang Jinhu Yang Research Center for Translational Medicine & Key Laboratory of Arrhythmias of the Ministry of Education of China East Hospital Tongji University School of Medicine Department of Energy and Power Engineering Tsinghua University School of Chemical Science and Engineering Tongji University Institute for Process Modelling and Optimization Jiangsu Industrial Technology Research Institute

Rational design of advanced polar hosts with high sulfur loading, facilitated ionic/electronic transport and effectively suppressed shuttling effect has great potential for high performance lithium-sulfur batteries,yet it remains challenging. Here we propose a novel templated spherical coassembly strategy to fabricate the MoS2/C hollow spheres as an efficient sulfur host material. The unique hollow structure provides enough interior space for accommodating a substantial amount of sulfur, and effectively suppresses the diffusion of dissolved polysulfides by both physical confinement and chemical adsorption. Moreover, the ionic transport as well as the ability to mitigate volume variation upon cycling is also improved, thereby maximizing the utilization of sulfur. Owing to these merits, when evaluated as a sulfur host for lithiumsulfur batteries, the MoS2/C hollow spheres exhibit appealing electrochemical performance with an impressive specific capacity of 1082 mA hg-1at 0.1 C, excellent rate capability and superior cycling stability with a low fading rate of 0.04% per cycle.

关键词： Lithium-sulfur batteries Cathode MoS2 C hollow spheres Physical confinement chemical adsorption

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An improved discrete artificial bee colony algorithm for hybrid flow shop problems

Communications in Computer and Information Science

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Communications in Computer and Information Science 2013年 355卷 294-302页

作者： Cui, Zhe Gu, Xingsheng Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai 200237 China

Being a typical NP-hard combinatorial optimization problem, the hybrid flow shop (HFS) problem widely exists in manufacturing systems. In this paper, we firstly establish the model of the HFS problem by employing the vector representation. Then an improved discrete artificial bee colony (IDABC) algorithm is proposed for this problem to minimize the makespan. In the IDABC algorithm, a novel differential evolution and a modified variable neighborhood search are studied to generating new solutions for the employed and onlooker bees. The destruction and construction procedures are utilized to obtain solutions for the scout bees. The simulation results clearly imply that the proposed IDABC algorithm is highly effective and efficient as compared to six state-of-the-art algorithms on the same benchmark instances. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Manufacture

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process monitoring of multimode processes using kernel independent component analysis

Process monitoring of multimode processes using kernel indep...

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8th International Symposium on advanced control of chemical processes, ADCHEM 2012

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

ISBN: (纸本)9783902823052

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. © 2012 IFAC.

关键词： process monitoring

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An immune inspired approach to 802.11 Wireless LANs coverage optimization

An immune inspired approach to 802.11 Wireless LANs coverage...

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2010 International Conference on Information, Networking and Automation, ICINA 2010

作者： Zhou, Xuan Qi, Rongbin Li, Qian Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China School of Electronics and Information Tongji University Shanghai China

ISBN: (纸本)9781424481057

Coverage optimization is a critical issue in 802.11 Wireless LANs planning problems. In this paper an immune network algorithm named opt-aiNet is studied in order to automatize the planning process by optimizing the BS's (Base Station) sites. Compared the results of opt-aiNet and genetic algorithms(GA) which have been used in radio coverage optimization before, we found that opt-aiNet could find the optimal solution all times while GA falling into local optimum solution sometimes, and opt-aiNet converged more quickly than GA in most cases. Experimental results show that optaiNet is an effective way to optimize the 802.11 Wireless LANs planning problems. © 2010 IEEE.

关键词： Genetic algorithms

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Parameter estimation of industrial PET reactor using multi-objective kernel density estimation of distribution algorithm

Parameter estimation of industrial PET reactor using multi-o...

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作者： Luo, Na Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Ministry of Education Shanghai 200237 China State-Key Laboratory of Chemical Engineering East China University of Science and Technology Shanghai 200237 China

With a multitude of reaction pathways, poly (ethylene-terephthalate) (PET) polymerization of industrial practice is complex, and the quality of PET is normally described in terms of several experimentally measured indices. In this paper, parameters estimation of industrial PET reactors is presented as a multi-objective problem to make the mathematic model consistent with the actual industrial process. Considering the interrelation among parameters and the failure of general optimization algorithms, a new multi-objective estimation of distribution algorithm is proposed. Kernel density estimation is used to make the new population more suitable for real-life problems instead of Gaussian model during the evolution of the algorithm. Strategies including selection of kernel width, sampling method and Pareto domination selection are used to explore and exploit the search space more efficiently. With industrial operating data identified in steady state and eliminated from gross error, kinetic parameters are estimated by minimizing carboxyl end group concentration and degree of polymerization simultaneously using the proposed algorithm. The simulation results show that the model with estimated parameters has better predictive performance compared with the experimental parameters. Copyright © 2011 Curtin University of Technology and John Wiley & Sons, Ltd. Copyright © 2011 Curtin University of Technology and John Wiley & Sons, Ltd.

关键词： Parameter estimation

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Recovering from Feedback Failure in Minimal Time

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IFAC-PapersOnLine 2016年第18期49卷 612-617页

作者： Yu, Zhaoxu Hammer, Jacob Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology No. 130 Meilong Road Shanghai City200237 China Department of Electrical and Computer Engineering University of Florida GainesvilleFL32611-6130 United States

It is well known that feedback failure increases operating errors in control systems. The objective here is to develop controllers that reduce such operating errors in minimal time, once feedback has been restored. It is shown that there are robust optimal feedback controllers that attain this objective, and that the performance of these controllers can be approximated as closely as desired by bang-bang controllers that are easy to derive and implement. © 2016

关键词： Feedback controllers Nonlinear systems optimization Bang bang controllers Operating errors Optimal controls Optimal Feedback

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Fuzzy dynamic characteristic model based attitude control of hypersonic vehicle in gliding phase

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Science China(Information Sciences) 2011年第3期54卷 448-459页

作者： LUO Xiong 1,2 & LI Jiang 1 1 Department of Computer Science and Technology, key laboratory of advanced control of Iron and Steel process (ministry of education), University of Science and Technology Beijing, Beijing 100083, China 2 National laboratory of Space Intelligent control, Beijing 100190, China 1. Department of Computer Science and Technology Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) University of Science and Technology Beijing Beijing 100083 China2. National Laboratory of Space Intelligent Control Beijing 100190 China

The intelligent autonomous control of hypersonic vehicles has aroused great interest from the field of spacecraft. To solve the problem of longitudinal attitude control of hypersonic vehicle in gliding phase, a new intelligent controller is proposed in this paper. This new controller is based on the fuzzy dynamic characteristic modeling method. The fuzzy logic is introduced into the characteristic modeling by dividing the whole restriction range into several subspaces. Simulations show that this modification greatly improves the performance of the original method. With the same whole restriction range the fuzzy dynamic characteristic modeling decreases the time of convergence, and at the same time makes the attitude angle tracing more precise and robust. Since the sub-model is a characteristic model that has stronger adaptiveness than a fixed local model, the number of fuzzy rules is greatly reduced. Our model sharply reduces the complexity in constructing a fuzzy dynamic model. Finally, simulation results are given to show the effectiveness of the proposed approach in dealing with the attitude control problem of hypersonic vehicle in gliding phase.

关键词： hypersonic vehicle gliding attitude control fuzzy dynamic characteristic modeling

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L2- L∞ State Estimation for Discrete-time Delayed Neural Networks with Missing Measurements and Randomly Occurring Sensor Linearity

L2- L∞ State Estimation for Discrete-time Delayed Neural Ne...

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第35届中国控制会议

作者： Hao Zhang Huaicheng Yan Hongbo Shi Hao Zhang Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education Department of Control Science and Engineering Tongji University

ISBN: (纸本)9781509009107

This paper is concerned with the L-L state estimation problem for discrete-time delay neural networks with missing measurements and randomly occurring sensor *** phenomena of missing measurements and randomly occurring sensor linearity are constructed with two sequences of random variables,which obey the partial Bernoulli distribution.A sufficient condition is firstly given such that the augmented filtering error system is stochastically stable with a guaranteed optimal L-L performance by solving a set of linear matrix inequalities(LMIs).Finally,a simulation example is given to show the effectiveness of the proposed method.

关键词： L2-L∞ state estimation discrete-time delayed neural networks missing measurements randomly occurring sensor linearity

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