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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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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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Three Stage Equilibrium Model for Coal Gasification in Entrained Flow Gasifiers Based on Aspen Plus

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Chinese Journal of chemical Engineering 2013年第1期21卷 79-84页

作者：孔祥东钟伟民杜文莉钱锋 Key Laboratory of Advanced Control and Optimization for Chemical Processes (Ministry of Education) East China University of Science and Technology Automation Institute East China University of Science and Technology

A three stage equilibrium model is developed for coal gasification in the Texaco type coal gasifiersbased on Aspen Plus to calculate the composition of product gas, carbon conversion, and gasification teml^erature. The model is divided into three stages including pyrolysis and combustion stage, char gas reaction stage, and gas *** reaction stage. Part of the water produced in thepyrolysis and combust!on stag.e is assumed to be involved inthe second stage to react with the unburned carbon. Carbon conversion is then estimated in the second stage by steam participation ratio expressed as a function of temperature. And the gas product compositions are calculated from gas phase reactions in the third stage. The simulation results are consistent with published experimental data.

关键词： coal gasification Texaco gasifier equilibrium model carbon conversion product gas composition

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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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Modified Self-adaptive Immune Genetic Algorithm for optimization of Combustion Side Reaction of p-Xylene Oxidation

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Chinese Journal of chemical Engineering 2012年第6期20卷 1047-1052页

作者：陶莉莉孔祥东钟伟民钱锋 Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and Technology Automation Institute East China University of Science and Technology

In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation factor suffers from the problem of premature convergence. In this study, a modified self-adaptive immune genetic algorithm (MSIGA) with two memory bases, in which immune concepts are applied to determine the mutation parameters, is proposed to improve the searching ability of the algorithm and maintain population diversity. Performance comparisons with other well-known population-based iterative algorithms show that the proposed method converges quickly to the global optimum and overcomes premature problem. This algorithm is applied to optimize a feed forward neural network to measure the content of products in the combustion side reaction of p-xylene oxidation, and satisfactory results are obtained.

关键词： self-adaptive immune genetic algorithm artificial neural network measurement p-xylene oxidation process

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Integral control on nonlinear spaces: two extensions

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IFAC-PapersOnLine 2016年第18期49卷 1000-1005页

作者： Zhang, Zhifei Ling, Zhihao Sarlette, Alain Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Department of Electronics & Information Systems Ghent University Shanghai China Key Laboratory of A.C.O.C.P. ECUST Shanghai China Department of Electronics & Information Systems Ghent University QUANTIC lab INRIA Paris France

This paper applies the recently developed framework for integral control on nonlinear spaces to two non-standard cases. First, we show that perfect target stabilization in presence of actuation bias holds also if this bias is state dependent. This might not be surprising, but in practice it provides an easy way to robustly cancel nonlinear dynamics of the uncontrolled plant. We specifically illustrate this for robust stabilization of a pendulum at arbitrary angle. Second, as previous work has been restricted to systems with as many control inputs as configuration dimensions, we here provide results for integral control of a non-holonomic system. More precisely, we design robust steering control of a rigid body under velocity bias. © 2016

关键词： Feedback linearization Lie groups Stabilization Arbitrary angles control inputs Geometric control Integral control Nonholonomic systems Robust stabilization State dependent Steering control

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Improved Kernel PLS-based Fault Detection Approach for Nonlinear chemical processes

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Chinese Journal of chemical Engineering 2014年第6期22卷 657-663页

作者：王丽侍洪波 School of Electrical and Electronic Engineering Shanghai Institute of Technology Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

In this paper, an improved nonlinear process fault detection method is proposed based on modified kernel partial least squares(KPLS). By integrating the statistical local approach(SLA) into the KPLS framework, two new statistics are established to monitor changes in the underlying model. The new modeling strategy can avoid the Gaussian distribution assumption of KPLS. Besides, advantage of the proposed method is that the kernel latent variables can be obtained directly through the eigen value decomposition instead of the iterative calculation, which can improve the computing speed. The new method is applied to fault detection in the simulation benchmark of the Tennessee Eastman process. The simulation results show superiority on detection sensitivity and accuracy in comparison to KPLS monitoring.

关键词： nonlinear process fault detection kernel partial least squares statistical local approach

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Novel control Vector Parameterization Method with Differential Evolution Algorithm and Its Application in Dynamic optimization of chemical processes

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Chinese Journal of chemical Engineering 2013年第1期21卷 64-71页

作者：孙帆钟伟民程辉钱锋 Key Laboratory of Advanced Control and Optimization for Chemical Processes (Ministry of Education) East China University of Science and Technology Department of Automation East China University of Science and Technology

Two general approaches are adopted in solving dynamic optimization problems in chemical processes, namely, the analytical and numerical methods. The numerical method, which is based on heuristic algorithms, has been widely used. An approach that combines differential evolution （DE） algorithm and control vector parameteri- zation （CVP） is proposed in this paper. In the proposed CVP, control variables are approximated with polynomials based on state variables and time in the entire time interval. Region reduction strategy is used in DE to reduce the width of the search region, which improves the computing efficiency. The results of the case studies demonstrate the feasibility and efficiency of the oroposed methods.

关键词： control vector pararneterization differential evolution algorithm dynamic optimization chemical processes

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Self-adaptive iterative hybrid modeling and its application in acetylene hydrogenation process

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Huagong Xuebao/CIESC Journal 2018年第11期69卷 4814-4822页

作者： Guo, Jingjing Xu, Jinjin Du, Wenli Ye, Zhencheng State Key Laboratory of Chemical Engineering Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai200237 China

The reaction mechanism of chemical process is complex. There is a modeling error between the mechanism model and the actual reaction system. At the same time, there are complex slow time-varying features, such as catalyst deactivation, fuel coking, etc. Thus there will be a mismatch between the process model and the actual process system. A self-adaptive iterative hybrid model (SAIHM) is established to reflect the dynamic characteristics of the process accurately over a long period. The mechanism model and the data-driven model are effectively combined to improve the prediction accuracy of the model;the data-driven model uses the deep recurrent neural network (DRNN) to fully exploit the timing relationship between adjacent conditions;the data-driven model is automatically updated based on the evaluation indicators to resolve the contradiction between accuracy and efficiency. The simulation and comparison results of the self-adaptive iterative hybrid model and the existing mechanism model established based on the historical operation data of an acetylene hydrogenation adiabatic reactor show that the self-adaptive iterative hybrid model can more effectively track the actual system. © All Right Reserved.

关键词： Dynamics

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On set stabilization for genetic regulatory networks 35

On set stabilization for genetic regulatory networks

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第35届中国控制会议

作者： LI Fangfei LI Jianning YU Zhaoxu School of Automation Hangzhou Dianzi University Department of Mathematics East China University of Science and Technology Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

ISBN: (纸本)9781509009107

Set stabilization for Boolean networks which is a kind of genetic regulatory networks is considered in this paper. An algorithm is provided to achieve the set stability for Boolean networks by changing the columns of the transition matrices of Boolean networks. Then, pinning nodes can be selected. Furthermore, pinning control design algorithm is given. Finally, the model for infection of the bacterium is presented to illustrate the effectiveness of the proposed results.

关键词： Boolean networks set stabilization pinning control semi-tensor product

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