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

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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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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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A Semi-physical Simulation Testbed tor Cybersecurity

A Semi-physical Simulation Testbed tor Cybersecurity

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第37届中国控制会议

作者： Yunfei Wang Zhengdao Zhang Linbo Xie Key Laboratory of Advanced Process Control for Light Industry Ministry of EducationJiangnan University

With a massive influx of cyber threats to SCADA systems,the cybersecurity of critical infrastructures has become one of the most addressed *** is impossible to conduct cybersecurity research through injecting attacks into real SCADA ***,a reliable and efficient testbed is crucial for cybersecurity ***,the existing testbeds have some problems,such as high cost,poor portability,and lack adjustability for different *** may not guarantee them to be spread *** overcome these problems,we propose a semi-physical simulation *** components of the SCADA system and plant are simulated by raspberry 3 B in proposed *** communication way among raspberry 3 B employs Modbus/Tcp by physical links,which makes attack simulation more *** virtual plant of the proposed testbed corresponds to a boiler-turbine *** performances of the boiler-turbine unit in open loop and close loop are verified in the proposed *** addition,few work has been done to verify the impact of attacks on virtual or physical plants to ensure that the testbed accurately simulates a real ***,we inject the Data modification attack,the Replay attack and the Blocking attack into the proposed testbed to explore their damages on boiler-turbine unit,and verify the reliable of the proposed testbed for simulating attacks.

关键词： Testbed Cyber-attacks SCADA Cybersecurity Modbus/Tcp

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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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Predicting bruise susceptibility in apples using Vis/SWNIR technique combined with ensemble learning

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International Journal of Agricultural and Biological Engineering 2017年第5期10卷 144-153页

作者： Yao Jian Guan Jiyu Zhu Qibing Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) Jiangnan UniversityWuxi 214122China

Bruise susceptibility in fruits is an important indicator in evaluating risk factors for bruising caused by external *** of the bruising susceptibility of fruit can provide useful information for proper postharvest handling and storage *** this study,visible and shortwave near-infrared(Vis/SWNIR)technique was used to develop nondestructive method for predicting the bruise susceptibility of ***/SWNIR spectra covering 400-1100 nm were collected for 300‘Golden Delicious’apples over a time period of three weeks after harvest.A pendulum-like device was used to simulate impact bruise at three impact energy levels of 1.11 J,0.66 J and 0.33 *** volumes were estimated from the digital images of the bruised apples by using the bruise thickness *** prediction models,*** least squares model(PLS),partial least squares model combined with successful projection algorithm(SPA-PLS),and selective ensemble learning based on feature selection(SELFS),for bruise susceptibility were developed for each impact energy level as well as for the pooled *** with PLS and SPA-PLS model,SELFS gave the better prediction results for bruise susceptibility,with the correlation coefficient of R_(p)=0.800-0.886 for the prediction set,the root-mean-square error of 38.7-62.1 mm^(3)/J for the prediction set(RMSEP),and the residual predictive deviation(RPD)of 1.78-2.14 for three impact energy *** three impact energy levels,the RMSEP and RPD value obtained by SELFS model improved by 14.8%-20.0%and 15.0%-24.5%compared to PLS model,and 11.4%-21.2%and 11.5%-27.1%compared to SPA-PLS model,*** SELFS model achieved relatively lower prediction accuracies for the pooled data,with the R_(p) values of 0.731,RMSEP of 85.46 mm^(3)/J,and RPD of 1.46,which were also better than that of PLS model and SPA-PLS *** research demonstrated that Vis/SWNIR technique combined with ensemble learning is promising technique for rapid assessment of

关键词： apple nondestructive detection bruise susceptibility visible/short-wave near-infrared technique ensemble learning

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Multi-objective optimization of p-xylene oxidation process using an improved self-adaptive differential evolution algorithm

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Chinese Journal of chemical Engineering 2017年第8期25卷 983-991页

作者： Lili Tao Bin Xu Zhihua Hu Weimin Zhong College of Engineering Shanghai Polytechnic University School of Mechanical Engineering Shanghai University of Engineering Science Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology

The rise in the use of global polyester fiber contributed to strong demand of the Terephthalic acid （TPA）. The liquid-phase catalytic oxidation of p-xylene （PX） to TPA is regarded as a critical and efficient chemical process in industry [ 1 ]. PX oxidation reaction involves many complex side reactions, among which acetic acid combustion and PX combustion are the most important. As the target product of this oxidation process, the quality and yield of TPA are of great concern. However, the improvement of the qualified product yield can bring about the high energy consumption, which means that the economic objectives of this process cannot be achieved simulta- neously because the two objectives are in conflict with each other. In this paper, an improved self-adaptive multi-objective differential evolution algorithm was proposed to handle the multi-objective optimization prob- lems. The immune concept is introduced to the self-adaptive multi-objective differential evolution algorithm （SADE） to strengthen the local search ability and optimization accuracy. The proposed algorithm is successfully tested on several benchmark test problems, and the performance measures such as convergence and divergence metrics are calculated. Subsequently, the multi-objective optimization of an industrial PX oxidation process is carried out using the proposed immune self-adaptive multi-objective differential evolution algorithm （ISADE）. optimization results indicate that application oflSADE can greatly improve the yield of TPA with low combustion loss without degenerating TA quality.

关键词： p-Xylene oxidation Operation condition optimization Multi-objective optimization Self-adaptive differential evolution

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Iterative Learning Fault Estimation Algorithm for Time-delay Systems Based on Extended Observer

Iterative Learning Fault Estimation Algorithm for Time-delay...

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Data Driven control and Learning Systems (DDCLS)

作者： Hongfeng Tao Qiang Wei Key laboratory of Advanced Process Control for Light Industry(Ministry of Education) Jiangnan University Wuxi

ISBN: (纸本)9781538626191

For a class of multivariable linear, time-delay systems with actuator fault and measurement bounded disturbances in output, an iterative learning fault estimation algorithm based on extended observer is proposed. The extended observer is designed in terms of the linear matrix inequality technique such that the states and disturbances can be estimated simultaneously in every trials, then the faults and disturbances can be separated for avoiding impact to each other. Afterwards, the iterative learning fault estimation algorithm by defining estimation residual is chosen to adaptively approximate the actuator fault with initial error, then the necessary and sufficient conditions for the existence of the learning algorithm is given through λ norm theory and Bellman-Gronwall inequality, and the uniform convergence criteria of the control algorithm is also discussed. Simulation results verify the feasibility and effectiveness of this algorithm.

关键词： Observers Iterative algorithms Actuators Linear matrix inequalities Approximation algorithms Heuristic algorithms

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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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