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An on-line constraint softening strategy to guarantee the feasibility of dynamic controller in double-layered MPC

Chinese Journal of chemical Engineering 2017年第12期25卷 1805-1811页

作者： Hongguang Pan Weimin Zhong Zaiying Wang School of Electrical and Control Engineering Xi'an University of Sdence and Technology Xi'an 710071 China Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Sdence and Technology Shanghai 200237 China

A double-layered model predictive control(MPC), which is composed of a steady-state target calculation(SSTC)layer and a dynamic control layer, is a prevailing hierarchical structure in industrial process control. Based on the reason analysis of the dynamic controller infeasibility, an on-line constraints softening strategy is given. At first, a series of regions of attraction(ROA) of the dynamic controller is calculated according to the softened constraints;then a minimal ROA containing the current state is chosen and the corresponding softened constraint is adopted by the dynamic controller. Note that, the above measures are performed on-line because the centers of the above ROA are the steady-state targets calculated at each instant. The effectiveness of the presented strategy is illustrated through two examples.

关键词： Model predictive control Steady-state target calculation Dynamic control Feasibility Region of attraction

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Distillation Sequence optimization Considering Extractive Distillation under Multiple Conditions: A Methanol to Propylene Case Study

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China Petroleum processing & Petrochemical Technology 2019年第4期21卷 88-93页

作者： Yu Jing Qian Feng Wang Jiming Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of EducationEast China University of Science and TechnologyShanghai 200237 Coteva AgriscienceTM Shanghai 201203 School of Chemical Engineering East China University of Science and TechnologyShanghai 200237

This study provides insights into the distillation sequence optimization of refinery system in a methanol to propylene plant with extractive distillation under multiple conditions. The simulated annealing algorithm(SA) with relative cost function was used to solve a meaningful optimization problem. It was observed that different conditions had differed on the flowsheet. Case study shows the effectiveness of the proposed method.

关键词： distillation sequence optimization simulated annealing algorithm MATLAB multiple conditions

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A New Liquid Level Measurement Method Based on Randomized Hough Transform 29

A New Liquid Level Measurement Method Based on Randomized Ho...

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第29届中国控制与决策会议

作者： Geng Dongdong Luo Na Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

ISBN: (纸本)9781509046584

Traditional level measurements based on sensors were easily affected by circumstance especially in severe industrial process,whose accuracy of measurement cannot meet the control *** order to deal with the problem,a new level measurement method based on randomized Hough Transform was *** pre-processing,noise-reduction and filtering to the original image,the randomized Hough Transform was used to recognize the liquid *** results showed that the error of the proposed method is within 2%and the average recognition time is within 0.1 *** proposed method can meet the requirement in industrial fields.

关键词： Randomized Hough Transform Level Measurement Low-pass Filter

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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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Stable Distributed Model Predictive control Strategy Based on Agent Coordination 33

Stable Distributed Model Predictive Control Strategy Based o...

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第三十三届中国控制会议

作者： WANG Mengling SHI Hongbo Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

ISBN: (纸本)9781479947249

Many systems composed by several interacting subsystems are usually controlled by a distributed control framework. Distributed Model Predictive control(DMPC) strategy, in which each subsystem is controlled by a local MPC controller, has advantages of accommodating constraints, less computational cost and high flexibility. In order to improve the global performance and guarantee the system stability, a stabilized DMPC strategy is proposed in this paper, in which subsystems interact through inputs. At first, local initial feasible solutions are achieved based on a Minkowski functional to guarantee the local closed-loop system stabilization. And then the global optimal solutions are obtained through coordination strategy for the sake of reducing iteration time and accelerating the convergence speed efficiently. Finally, the accuracy and efficiency of the proposed scheme is put to test through simulation.

关键词： Distributed model predictive control,agent coordination,Stability

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Neural Network based Model Predictive control of Spatially Cellular Uptake in Tissue Engineering 36

Neural Network based Model Predictive Control of Spatially C...

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第36届中国控制会议

作者： WANG Mengling Yan Huaicheng SHI Hongbo Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

ISBN: (纸本)9781538629185

In this paper,a neural network based model predictive control（MPC） strategy is proposed to for the cellular uptake（as a function of space and time） of a ***,a time/space separation method is used to transform the high-dimensional spatiotemporal data into low-dimensional temporal ***,the MPC strategy is posed using the identified temporal radial basis function neural network *** the solution of NN-based MPC is obtained by a golden section method that can shorten the solution time of the optimization *** accuracy and effectiveness of this approach are demonstrated on an example motivated by tissue engineering.

关键词： Cellular uptake rate distributed parameter system model predictive control neural network

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第29届中国控制与决策会议

作者： Shuai Zhao Bing Song Hongbo Shi Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and TechnologyMinistry of Education

ISBN: (纸本)9781509046584

Quality-related fault detection has received extensive attention in recent years. It requires an appropriate supervisory relationship between process variables and quality variables. While the traditional principal component analysis(PCA) doesn't consider the relationships between them. Thus we proposed the mutual information principal component analysis(MIPCA) to detect the quality-related faults. MIPCA fully integrates the advantages of mutual information(MI) and PCA. With MIPCA, process variables can be utilized to monitor the process under the supervision of quality variables and judge a fault is whether related to the quality or not. Finally, the feasibility and effectiveness of the MIPCA are verified in Tennessee Eastman process(TEP).

关键词： Quality-related Principal component analysis Mutual information Fault detection

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Privacy preserving consensus under interception attacks 36

Privacy preserving consensus under interception attacks

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第36届中国控制会议

作者： Han Zhou Wen Yang Chao Yang Key Laboratory of Advanced Control and Optimization for Chemical Processes(East China University of Science and Technology) Ministry of Education

ISBN: (纸本)9781538629185

In this paper,we consider the privacy preserving problem of consensus ***,we introduce a privacy preserving scheme,where each node produces and transmits a sequence of random values with their mean equaling to the node's initial *** show that the network can reach average consensus with privacy preserving scheme,and provide a sufficient condition under which the initial state of one node can be inferred ***,we study the privacy preserving performance when there exists an attacker who can intercept the data transmitted on the *** a ring network,aiming at the attacker with limited power,we find the optimal attacking strategy to maximize the probability of the privacy ***,the simulations verify the derived theoretical results.

关键词： Privacy preserving Consensus protocol Interception attack

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Modeling and optimization of the Steam Turbine Network of an Ethylene Plant

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Chinese Journal of chemical Engineering 2013年第5期21卷 520-528页

作者：李泽秋赵亮杜文莉钱锋 Key Laboratory of Advanced Control and Optimization for chemical Process (hTlinistry of t~ducation) East ChinaUniversity of Science and Technology Shanghai 200237 China

In this paper,we developed a hybrid model for the steam turbines of a utility system,which combines an improved neural network model with the thermodynamic ***,a nonlinear programming(NLP) model of the steam turbine network is formulated by utilizing the developed steam turbine models to minimize the total steam cost for the whole steam turbine ***,this model is applied to optimize the steam turbine network of an ethylene *** obtained results demonstrate that this hybrid model can accurately estimate and evaluate the performance of steam turbines,and the significant cost savings can be made by optimizing the steam turbine network operation at no capital cost.

关键词： hybrid model steam turbine network utility system economic objective

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L2- L∞state estimation for discrete-time delayed neural networks with missing measurements and randomly occurring sensor linearity 35

L2- L∞state estimation for discrete-time delayed neural net...

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35th Chinese control Conference, CCC 2016

作者： Zhang, Hao Yan, Huaicheng Shi, Hongbo Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education Shanghai200237 China Department of Control Science and Engineering Tongji University Shanghai200092 China

ISBN: (纸本)9789881563910

This paper is concerned with the L2- L∞state estimation problem for discrete-time delay neural networks with missing measurements and randomly occurring sensor linearity. The 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 L2- 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. © 2016 TCCT.

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

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