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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Hualiang Guo Wangli He The Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China

The scaled consensus problem for second-order multi-agent systems is studied in this paper. A novel scaled consensus algorithm combining impulsive control and sampled control is proposed to make the agents' states achieve a common quantity but of their own scales. In the proposed algorithm, a special function, named intermittent function, is introduced to represent the control duration and the rest duration. Specifically, by selecting special functions as the proposed intermittent functions, the scaled consensus algorithm can drop into impulsive control or sampled control. Several necessary and sufficient conditions are derived to ensure scaled consensus of the controlled second-order multi-agent systems under directed graph. An example is provided to validate the theoretical analysis.

关键词： Multi-agent systems Convergence Graph theory control systems Satellites Continuous time systems Nickel

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Weighted Semi-supervised Orthogonal Factor Analysis Model for Quality-Related Process Monitoring

Weighted Semi-supervised Orthogonal Factor Analysis Model fo...

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Chinese control Conference (CCC)

作者： Xiaohui Cui Jian Yang Hongbo Shi Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education Ecust China University of Science and Technology Shanghai China

Probabilistic model has already been widely used for process monitoring. However, the obtained factors may contain quality-unrelated information, which is harmful to the quality-related process monitoring. Meanwhile, considering the situation of unequal sample rates of process and quality variables, a semi -supervised orthogonal factor analysis (Semi -SOFA) model is presented, further, to improve robustness, Semi-SOFA is extended to weighted form (WSemi-SOFA). This paper performs orthogonal decomposition on the obtained factors, which divides them into two parts: quality-related one and quality-unrelated one. Based on it, the corresponding T 2 statistics are designed to offer quality-related process monitoring, respectively. Besides, SPE statistics are constructed as supplement to monitor residuals. For effectiveness demonstration of the proposed method, TE benchmark is utilized.

关键词： Data models Monitoring Analytical models Probabilistic logic Robustness Predictive models Principal component analysis

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Observer-Based Adaptive Output-Feedback Quantized control for Switched Stochastic Nonlinear Time-Delay Systems

Observer-Based Adaptive Output-Feedback Quantized Control fo...

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第37届中国控制会议

作者： Yekai Yang Zhaoxu Yu Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education Department of AutomationEast China University of Science and Technology

This paper is concerned with the adaptive output-feedback tracking control problem for switched stochastic nonlinear time-delay systems under arbitrary switching in the presence of input and output *** common Lyapunov-Krasoviskii functional approach,neural network(NN) approximation-based method and backstepping technique,a novel observer-based adaptive output-feedback controller is presented to guarantee that all signals of closed-loop systems are4-moment(or 2-moment) semi-globally uniformly ultimately bounded(SGUUB) and the tracking error can converge to a small neighborhood of the ***,a simulation example is given to verify the effectiveness of the proposed methodology.

关键词： Switched stochastic systems Adaptive quantized control Output-feedback Time-delay Lyapunov-Krasoviskii functional

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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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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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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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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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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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Fundamental Theories and key Technologies for Smart andOptimal Manufacturing in the Process Industry

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Engineering 2017年第2期3卷 154-160页

作者： Feng Qian Weimin Zhong Wenli Du Key Laboratory of Aflvanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and TechnologyShanghai 200237 China

Given the significant requirements for transforming and promoting the process industry, we present themajor limitations of current petrochemical enterprises, including limitations in decision-making, produc-tion operation, efficiency and security, information integration, and so forth. To promote a vision of theprocess industry with efficient, green, and smart production, modern information technology should beutilized throughout the entire optimization process for production, management, and marketing. To focuson smart equipment in manufacturing processes, as well as on the adaptive intelligent optimization of themanufacturing process, operating mode, and supply chain management, we put forward several key scien-tific problems in engineering in a demand-driven and application-oriented manner, namely：intelligentsensing and integration of all process information, including production and management information; collaborative decision-making in the supply chain, industry chain, and value chain, driven by knowledge; cooperative control and optimization of plant-wide production processes via human-cyber-physical in-teraction; and Q life-cycle assessments for safety and environmental footprint monitoring, in addition totracing analysis and risk control. In order to solve these limitations and core scientific problems, we furtherpresent fundamental theories and key technologies for smart and optimal manufacturing in the processindustry. Although this paper discusses the process industry in China, the conclusions in this paper can beextended to the larocess industry around the world.

关键词： Process industry Smart and optimal manufacturing Green manufacturing High-end manufacturing Optimality assessment

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Performance monitoring of non-gaussian chemical processes with modes-switching using globality-locality preserving projection

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Frontiers of chemical Science and Engineering 2017年第3期11卷 429-439页

作者： Xin Peng Yang Tang Wenli Du Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai 200237 China

In this paper, we propose a novel performance monitoring and fault detection method, which is based on modified structure analysis and globality and locality preserving （MSAGL） projection, for non-Gaussian processes with multiple operation conditions. By using locality preserving projection to analyze the embedding geometrical manifold and extracting the non-Gaussian features by independent component analysis, MSAGL preserves both the global and local structures of the data simultaneously. Furthermore, the tradeoff parameter of MSAGL is tuned adaptively in order to find the projection direction optimal for revealing the hidden structural information. The validity and effectiveness of this approach are illustrated by applying the proposed technique to the Tennessee Eastman process simulation under multiple operation conditions. The results demonstrate the advantages of the proposed method over conventional eigendecomposition-based monitoring methotis.

关键词： non-Gaussian processes subspace projection independent component analysis locality preserving projection finite mixture model

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