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第29届中国控制与决策会议

作者： Yupeng Du Zhenlei Wang Xin Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Center of Electrical & Electronic Technology Shanghai Jiao Tong University

ISBN: (纸本)9781509046584

The disturbance in chemical process is complex and has the multiple characteristics,and the control performance assessment of multivariable system with multiple disturbances is one of the hot *** this paper,the control performance assessment method of multivariable systems,based on multi-time-variant-disturbances mixing generalized minimum variance(MMGMV),is ***,the generalized minimum variance control is introduced into the multivariable system performance assessment,and the weight matrix is designed according to the time-varying control ***,the multivariable MMGMV controller is designed combining with the idea of multi-model weights mixing for all multi-time-varying ***,the output variance of each controlled variable is obtained using MMGMV *** average variance of controlled variable in the MMGMV controller acts as the criterion of performance assessment,and combining with the output variance of actual controller for the controller performance *** with the minimum variance benchmark,the developed method is more reasonable and practical for the control performance assessment of multivariable *** developed approach is demonstrated by a numerical simulation and a heavy oil fractionation of process control system.

关键词： Multivariable Multi-time-variant-disturbance-mixing Generalized minimum variance Time-varying weight matrix Mixing weight

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A class of nonlinear discrete-time system adaptive control based on second level multiple models 36

A class of nonlinear discrete-time system adaptive control b...

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第36届中国控制会议

作者： Yong Chen Xin Wang Zhenlei Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Center of Electrical and Electronic Technology Shanghai Jiao Tong University

ISBN: (纸本)9781538629185

Using multiple models to deal with transients for adaptive systems which is large parametric uncertainties was introduced in the 1990 *** common method is using switching ***,these methods has some potential *** this paper,a new multiple models scheme is proposed for a class strict-feedback nonlinear discrete-time ***,we use feedback linearization and backstepping method to develop adaptive indirect schemes with an observer-based identifier to ***,we design a controller based on the convex hull of parameter *** the number of necessary models is less than switching scheme,and can use the information of all identification ***,simulation have demonstrated that this method is effectively to a class of strict-feedback nonlinear discrete-time system.

关键词： convex hull multiple models backstepping nonlinear system strict-feedback

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Second Level Adaptive control Based on Combination Multiple Model 29

Second Level Adaptive Control Based on Combination Multiple ...

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第29届中国控制与决策会议

ISBN: (纸本)9781509046584

Since all of adaptive models converge to the same point in parameter space,classical second level multiple model adaptive control method cannot deal with linear time-varying *** order to deal with this drawback,this paper proposes a modified second level adaptive control method based on combining the advantages of adaptive model and fixed model for a class linear discrete time-varying plant where only a little prior information which is ***,multiple adaptive models are selected in the space of parameters,and the parameters are identifying and the controller is designed based on second level adaptive ***,when one of sub-model of the adaptive models are closed to the real parameters of the system,all of these adaptive models are fixed,and then the controller is designed based on multiple fixed ***,simulations have demonstrated that this method is effectively to a class of linear time-varying system.

关键词： adaptive model fixed model second level adaptive control multi-model

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Prediction Consensus-Based Distributed Kalman Filtering with Packet Loss 36

Prediction Consensus-Based Distributed Kalman Filtering with...

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第36届中国控制会议

作者： Sha Fan Huaicheng Yan Hao Zhang Mengling Wang Xisheng Zhan Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology College of Mechatronics and Control Engineering Hubei Normal University Department of Control Science and Engineering Tongji University

ISBN: (纸本)9781538629185

This paper is concerned with the problem of distributed state estimation for linear discrete system with packet loss.A state prediction consensus mechanism is introduced to promote the estimation *** applying matrix theory,a sufficient condition for the convergence of the estimation error system is ***,a numerical example is given to show the algorithm proposed in this paper has better consensus performance compared with a classical Kalman consensus filtering（KCF） by some simulations in real and packet-dropping cases,***,the influence of consensus coefficient and prediction consensus coefficient on the estimation error covariance are presented by simulation.

关键词： Distributed state estimation Packet loss Kalman consensus filtering（KCF） State prediction consensus mechanism

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The decoder performance comparison in the closed-loop BMI system based on MPC

The decoder performance comparison in the closed-loop BMI sy...

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第37届中国控制会议

作者： Hongguang Pan Wenyu Mi Jinggao Sun Baocang Ding College of Electric and Control Engineering Xi'an University of Science and Technology Key Laboratory of Advanced Control and Optimization Technology of Ministry of Education East China University of Science and Technology School of Electronic and Information Engineering Xi'an Jiaotong University

Brain-machine interface(BMI) can be used to translate the neural activities of the brain into the control signals for the artificial arm, aiming to offer the disabled patients greater interaction with the world. In recent years, some emerging technologies, such as back propagation(BP) neural network and recurrent neural networks(RNN) with long-short term memory(LSTM), have been adopted in many fields. Hence, we firstly design four decoders based on the classical Wiener filter and Kalman filter, and the emerging BP neural network and RNN with LSTM, and compare the performance of these decoders offline. Secondly, considering the advantages of the model predictive control(MPC), we design an auxiliary controller based on MPC algorithm to form a closed-loop BMI system, and compare the performance of four decoders online.

关键词： Decoder design Model predictive control Performance comparison Online Offline

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Adaptive Neural Output Feedback control for Nonstrict-Feedback Nonlinear Systems with Quantized Input 36

Adaptive Neural Output Feedback Control for Nonstrict-Feedba...

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第36届中国控制会议

作者： Yan Dong Zhaoxu Yu Fangfei Li Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology Department of Mathematics East China University of Science and Technology

ISBN: (纸本)9781538629185

This paper focuses on the problem of adaptive output feedback tracking control for a class of nonstrict-feedback nonlinear systems with unknown control coefficients and quantized input. The difficulty from the unknown control direction is solved by using the linear state transformation and the Nussbaum gain function（NGF） approach. Based on the combination of input-driven observer, backstepping technique, neural network（NN） parametrization and variable separation method, a novel adaptive output feedback quantized control scheme involving only one adaptive parameter is developed for such systems. The designed quantized controller ensures that all signals of closed-loop systems are semi-globally uniformly ultimately bounded（SGUUB）, and the tracking error converges to an adjustable neighborhood of the origin. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed control design.

关键词： Nonstrict-feedback systems quantized input signal output feedback adaptive control unknown control direction

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GPU-based coevolutionary particle swarm optimization 36

GPU-based coevolutionary particle swarm optimization

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第36届中国控制会议

作者： ZHAO Liang Zhu Yanxing ZHANG Jianyu Ye Zhencheng Key Laboratory of Advanced Control and Optimization for Chemical Process(Ministry of Education) East China University of Science and Technology Ethylene Plant of Jilin Petrochemical Company Ltd.PetroChina

ISBN: (纸本)9781538629185

Coevolutionary particle swarm optimization（CPSO） algorithm has been investigated and applied in the real world *** tackling the large-scale and complex real time optimization problems,the running time of CPSO algorithm is a *** this paper,Graphics Processing Unit（GPU） is introduced to provide speedup in order to meet the real time *** CPSO algorithm has been implemented on GPU concurrently using the CUDA *** performance and run time of CPU-based and GPU-based CPSO algorithms are compared in *** experiment result shows that the GPU-based parallel computation mode can shorten the run time of CPSO algorithm apparently.

关键词： GPU CUDA Particle swarm optimization Coevolutionary particle swarm optimization

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Initial-Parameter-Criterion based Gaussian Mixture Model Monitoring Method for Non-Gaussian Process

Initial-Parameter-Criterion based Gaussian Mixture Model Mon...

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第37届中国控制会议

作者： Ying Tian Wenli Du Shanghai Key Lab of Modern Optical System School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology

Gaussian mixture model(GMM) monitoring method is commonly used for non-Gaussian process monitoring. In GMM monitoring method, the final number of Gaussian components and the statistical distribution parameters are estimated through the improved Figueiredo-Jain(F-J) algorithm in the modeling phase. However, the data dimensionality of modern industry is high, the number of initial Gaussian components is large for the accuracy of the algorithm. Under this condition, the relative small number of samplings makes the denominator in the weight estimation formula of the improved F-J algorithm become zero and the algorithm suspends. To make the algorithm work well in an acceptable modeling time, we deduce the Initial-ParameterCriterion among initial Gaussian components, data dimension, sampling number and propose the Initial-Parameter-Criterion based GMM(IPC-GMM) monitoring method. The proposed monitoring method is used for TE process monitoring, simulation results reveal the effectiveness and necessity of IPC-GMM monitoring method.

关键词： non-Gaussian process monitoring Gaussian mixture model Initial-Parameter-Criterion

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Finite time boundedness of switched delay systems by sliding mode technique 36

Finite time boundedness of switched delay systems by sliding...

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第36届中国控制会议

作者： Haijuan Zhao Yugang Niu Tinggang Jia Key Laboratory of Advanced Control and Optimization for Chemical Process(East China University of Science and Technology) Ministry of Education Automation Division of Shanghai Electric Group Co. Ltd.

ISBN: (纸本)9781538629185

In this paper,the finite-time boundedness（FTB） problem of sliding mode control（SMC） is investigated for a class of switched delay systems subject to uncertain parameter and nonlinear perturbation.A SMC law is constructed to drive the state trajectories onto the integral sliding surface during a finite time *** FTB of the controlled systems on both reaching phase and siding motion phase are analyzed by means of average dwell time ***,a numerical example is given.

关键词： Switched delay system Finite time boundedness Sliding mode control Average dwell time

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A Typical Power Allocation for Distributed Filtering

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IFAC-PapersOnLine 2017年第1期50卷 10550-10555页

作者： Zhang Y. Yang W. Yang C. Wang X. Sha F. Tian Y. Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Shanghai 200237 China Department of Automation Shanghai Jiaotong University Shanghai 200240 China

In this paper, the problem of power allocation is considered for distributed estimation over a sensor network with limited power. An online power allocation scheme is introduced to optimize the power consumption, where the power distributed to each communication channel depends on the innovation value of the sender. First, an optimal estimator gain is designed for each sensor by minimizing the mean-squared estimation error covariance. Second, a sufficient condition is provided to guarantee the stability of networked system with online power allocation scheme. Finally, we compare the estimation performance of the proposed online power scheduling scheme with some typical offline power scheduling schemes. © 2017

关键词： Distributed estimation Modified algebraic Riccati equation (MARE) Power allocation Transmission probability

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