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Statistical process monitoring based on improved principal component analysis and its application to chemical processes

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2013年第7期14卷 520-534页

作者： Chu-dong TONG Xue-feng YAN Yu-xin MA Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

In this paper, a novel criterion is proposed to determine the retained principal components (PCs) that capture the dominant variability of online monitored data. The variations of PCs were calculated according to their mean and covariance changes between the modeling sample and the online monitored data. The retained PCs containing dominant variations were selected and defined as correlative PCs (CPCs). The new Hotelling's T2 statistic based on CPCs was then employed to monitor the process. Case studies on the simulated continuous stirred tank reactor and the well-known Tennessee Eastman process demonstrated the feasibility and effectiveness of the CPCs-based fault detection methods.

关键词： Fault detection Principal component analysis (PCA) Correlative principal components (CPCs) Tennessee Eastman process

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Total plant performance evaluation based on big data: Visualization analysis of TE process

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Chinese Journal of chemical Engineering 2018年第8期26卷 1736-1749页

作者： Mengyao Li Wenli Du Feng Qian Weiming Zhong Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology

The performance evaluation of the process industry, which has been a popular topic nowadays, can not only find the weakness and verify the resilience and reliability of the process, but also provide some suggestions to improve the process benefits and efficiency. Nevertheless, the performance assessment principally concentrates upon some parts of the entire system at present, for example the controller assessment. Although some researches focus on the whole process, they aim at discovering the relationships between profit, society, policies and so forth, instead of relations between overall performance and some manipulated variables, that is, the total plant performance. According to the big data of different performance statuses, this paper proposes a hierarchical framework to select some structured logic rules from monitored variables to estimate the current state of the process. The variables related to safety and profits are regarded as key factors to performance evaluation. To better monitor the process state and observe the performance variation trend of the process, a classificationvisualization method based on kernel principal component analysis(KPCA) and self-organizing map(SOM) is established. The dimensions of big data produced by the process are first reduced by KPCA and then the processed data will be mapped into a two-dimensional grid chart by SOM to evaluate the performance status. The monitoring method is applied to the Tennessee Eastman process. Monitoring results indicate that off-line and on-line performance status can be well detected in a two-dimensional diagram.

关键词： Performance evaluation Structured logic rules Hierarchical framework Multidimensional visualization KPCA–SOM

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Equipment selection knowledge base system for industrial styrene process

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Chinese Journal of chemical Engineering 2018年第8期26卷 1707-1712页

作者： Weimin Zhong Shuming Liu Feng Wan Zhi Li Key Laboratory of Advanced Control and Optimization for Chemical Processed of Ministry of Education East China University of Science and Technology

Equipment selection for industrial process usually requires the extensive participation of industrial experts and technologists, which causes a serious waste of resources. This work presents an equipment selection knowledge base system for industrial styrene process(S-ESKBS) based on the ontology technology. This structure includes a low-level knowledge base and a top-level interactive application. As the core part of the S-ESKBS, the low-level knowledge base consists of the equipment selection ontology library, equipment selection rule set and Pellet inference engine. The top-level interactive application is implemented using S-ESKBS, including the parsing storage layer, inference query layer and client application layer. Case studies for the industrial styrene process equipment selection of an analytical column and an alkylation reactor are demonstrated to show the characteristics and implementability of the S-ESKBS.

关键词： Equipment selection Ontology technology Knowledge base system Styrene process

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Fault diagnosis and process monitoring using a statistical pattern framework based on a self-organizing map

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Journal of Central South University 2015年第2期22卷 601-609页

作者：宋羽姜庆超颜学峰 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education(East China University of Science and Technology)

A multivariate method for fault diagnosis and process monitoring is proposed. This technique is based on a statistical pattern(SP) framework integrated with a self-organizing map(SOM). An SP-based SOM is used as a classifier to distinguish various states on the output map, which can visually monitor abnormal states. A case study of the Tennessee Eastman(TE) process is presented to demonstrate the fault diagnosis and process monitoring performance of the proposed method. Results show that the SP-based SOM method is a visual tool for real-time monitoring and fault diagnosis that can be used in complex chemical *** with other SOM-based methods, the proposed method can more efficiently monitor and diagnose faults.

关键词： statistic pattern framework self-organizing map fault diagnosis process monitoring

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Distributed formation control for a multi-agent system with dynamic and static obstacle avoidances

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Chinese Physics B 2014年第7期23卷 337-342页

作者：曹建福凌志浩袁宜峰高冲 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

Formation control and obstacle avoidance for multi-agent systems have attracted more and more attention. In this paper, the problems of formation control and obstacle avoidance are investigated by means of a consensus algorithm. A novel distributed control model is proposed for the multi-agent system to form the anticipated formation as well as achieve obstacle avoidance. Based on the consensus algorithm, a distributed control function consisting of three terms （formation control term, velocity matching term, and obstacle avoidance term） is presented. By establishing a novel formation control matrix, a formation control term is constructed such that the agents can converge to consensus and reach the anticipated formation. A new obstacle avoidance function is developed by using the modified potential field approach to make sure that obstacle avoidance can be achieved whether the obstacle is in a dynamic state or a stationary state. A velocity matching term is also put forward to guarantee that the velocities of all agents converge to the same value. Furthermore, stability of the control model is proven. Simulation results are provided to demonstrate the effectiveness of the proposed control.

关键词： multi-agent system formation control obstacle avoidance consensus theory

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Orthogonal nonnegative matrix factorization based local hidden Markov model for multimode process monitoring

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Chinese Journal of chemical Engineering 2016年第7期24卷 856-860页

作者： Fan Wang Honglin Zhu Shuai Tan Hongbo Shi Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

Traditional data driven fault detection methods assume that the process operates in a single mode so that they cannot perform well in processes with multiple operating modes. To monitor multimode processes effectively,this paper proposes a novel process monitoring scheme based on orthogonal nonnegative matrix factorization(ONMF) and hidden Markov model(HMM). The new clustering technique ONMF is employed to separate data from different process modes. The multiple HMMs for various operating modes lead to higher modeling *** proposed approach does not presume the distribution of data in each mode because the process uncertainty and dynamics can be well interpreted through the hidden Markov estimation. The HMM-based monitoring indication named negative log likelihood probability is utilized for fault detection. In order to assess the proposed monitoring strategy, a numerical example and the Tennessee Eastman process are used. The results demonstrate that this method provides efficient fault detection performance.

关键词： Multimode processFault detectionHidden Markov modelOrthogonal nonnegative matrix factorization

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A new improved Alopex-based evolutionary algorithm and its application to parameter estimation

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Journal of Central South University 2013年第1期20卷 123-133页

作者：桑志祥李绍军董跃华 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education (East China University of Science and Technology)

In this work, focusing on the demerit of AEA (Alopex-based evolutionary algorithm) algorithm, an improved AEA algorithm (AEA-C) which was fused AEA with clonal selection algorithm was proposed. Considering the irrationality of the method that generated candidate solutions at each iteration of AEA, clonal selection algorithm could be applied to improve the method. The performance of the proposed new algorithm was studied by using 22 benchmark functions and was compared with original AEA given the same conditions. The experimental results show that the AEA-C clearly outperforms the original AEA for almost all the 22 benchmark functions with 10, 30, 50 dimensions in success rates, solution quality and stability. Furthermore, AEA-C was applied to estimate 6 kinetics parameters of the fermentation dynamics models. The standard deviation of the objective function calculated by the AEA-C is 41.46 and is far less than that of other literatures' results, and the fitting curves obtained by AEA-C are more in line with the actual fermentation process curves.

关键词： Alopex evolutionary algorithm Alopex-based evolutionary algorithm clone selection parameter estimation

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chemical process dynamic optimization based on hybrid differential evolution algorithm integrated with Alopex

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Journal of Central South University 2013年第4期20卷 950-959页

作者：范勤勤吕照民颜学峰郭美锦 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education (East China University of Science and Technology)

To solve dynamic optimization problem of chemical process (CPDOP), a hybrid differential evolution algorithm, which is integrated with Alopex and named as Alopex-DE, was proposed. In Alopex-DE, each original individual has its own symbiotic individual, which consists of control parameters. Differential evolution operator is applied for the original individuals to search the global optimization solution. Alopex algorithm is used to co-evolve the symbiotic individuals during the original individual evolution and enhance the fitness of the original individuals. Thus, control parameters are self-adaptively adjusted by Alopex to obtain the real-time optimum values for the original population. To illustrate the whole performance of Alopex-DE, several varietal DEs were applied to optimize 13 benchmark functions. The results show that the whole performance of Alopex-DE is the best. Further, Alopex-DE was applied to solve 4 typical CPDOPs, and the effect of the discrete time degree on the optimization solution was analyzed. The satisfactory result is obtained.

关键词： evolutionary computation dynamic optimization differential evolution algorithm Alopex algorithm self-adaptivity

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Adaptive neural control for pure-feedback nonlinear time-delay systems with unknown dead-zone: a Lyapunov-Razumikhin method

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控制理论与应用（英文版） 2013年第1期11卷 18-26页

作者： Zhaoxu YU Jianxu LUO Ji LIU Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology

This paper addresses the problem of adaptive neural control for a class of uncertain pure-feedback nonlinear systems with multiple unknown state time-varying delays and unknown dead-zone. Based on a novel combination of the Razumikhin functional method, the backstepping technique and the neural network parameterization, an adaptive neural control scheme is developed for such systems. All closed-loop signals are shown to be semiglobally uniformly ultimately bounded, and the tracking error remains in a small neighborhood of the origin. Finally, a simulation example is given to demonstrate the effectiveness of the proposed control schemes.

关键词： Pure-feedback nonlinear systems Adaptive neural control Razumikhin functional Time-delay Deadzone

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Data-Driven Distributionally Robust Mixed-Integer control through Lifted control Policy

arXiv

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arXiv 2025年

作者： Ma, Xutao Ning, Chao Du, Wenli Shi, Yang Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China the Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China the Department of Mechanical Engineering University of Victoria VictoriaBCV8W 3P6 Canada

This paper investigates the finite-horizon distributionally robust mixed-integer control (DRMIC) of uncertain linear systems. However, deriving an optimal causal feedback control policy to this DRMIC problem is computationally formidable for most ambiguity sets. To address the computational challenge, we propose a novel distributionally robust lifted control policy (DR-LCP) method to derive a high-quality approximate solution to this DRMIC problem for a rich class of Wasserstein metric-based ambiguity sets, including the Wasserstein ambiguity set and its variants. In theory, we analyze the asymptotic performance and establish a tight non-asymptotic bound of the proposed method. In numerical experiments, the proposed DR-LCP method empirically demonstrates superior performance compared with existing methods in the literature. © 2025, CC BY.

关键词： Mixed-integer linear programming

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