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检索条件"任意字段=Symposium on Dynamics and Control of Process Systems"

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A hybrid method for process fault detection and diagnosis

A hybrid method for process fault detection and diagnosis

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10th IFAC symposium on dynamics and control of process systems, DYCOPS 2013

作者： Mallick, Md. Raihan Imtiaz, Syed A. Faculty of Engineering and Applied Science Memorial University of Newfoundland NL Canada

ISBN: (纸本)9783902823595

For process fault detection and diagnosis, a real time hybrid method based on Principle component analysis (PCA) and Bayesian belief network (BBN) is described. Upon successful identification of fault from PCA residual plot and Q statistics, information from the PCA contribution of each variable is passed to the BBN for root cause analysis. Pearl's message passing algorithm is used for belief updating. Early detection of fault, makes the methodology more reliable and robust during the process fault occurrence. The aim of this monitoring tool is to incorporate prior process knowledge along with the present observed evidence to come up with most plausible explanation of how the process is behaving. The effectiveness of the proposed method is demonstrated for a Dissolution tank model for different simulated scenarios by detecting and diagnosing the fault accurately. © IFAC.

关键词： Bayesian networks

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Optimizing control of a continuous polymerization reactor

Optimizing control of a continuous polymerization reactor

引用

10th IFAC symposium on dynamics and control of process systems, DYCOPS 2013

作者： Hashemi, R. Kohlmann, D. Engell, S. Dynamics and Operations Group Technische Universität Dortmund Germany

ISBN: (纸本)9783902823595

In this contribution we study the application of non-linear model predictive control to a continuous polymerization of acrylic acid in tubular reactors with multiple side injections of monomer. The background of this work is to transfer the polymerization from semi-batch to continuous operation. Model Predictive control (MPC) is the obvious candidate to control such a multi-input system. The reactor configuration and polymerization reaction make the application of MPC very challenging. The controller employs a discretized dynamic pde model of the process and optimizes the productivity of the plant online while keeping the product quality parameters within the predefined constraints. The spatial domain of the model is discretized by applying the Weighted Essentially Non Oscillatory (WENO) scheme. Besides testing the controller for a nominal case in which the control model is identical to the existing plant, the controller has been simulated for two model-plant mismatch cases, caused by fouling and feed impurities. For the both cases, a moving window estimation scheme is applied to estimate the unknown parameters and to update the model used by NMPC. The results show that the controller can increase the product throughput considerably and has a robust performance in the presence of the model-plant mismatch. Moreover, the effect of formulating the quality constraints as soft constraints is studied. © IFAC.

关键词： Parameter estimation

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Using Dynsim® to study the implementation of advanced control in a Propylene/Propane splitter

Using Dynsim® to study the implementation of advanced contr...

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10th IFAC symposium on dynamics and control of process systems, DYCOPS 2013

作者： Hinojosa, Aldo I. Odloak, Darci Department of Chemical Engineering University of São Paulo Av. Prof. Luciano Gualberto trv 3 380 61548 São Paulo Brazil

ISBN: (纸本)9783902823595

In the process industry, advanced control is usually implemented so that they ensure stability and constraints satisfaction. Moreover, a competitive global market and environmental regulations results in the necessity for the economic optimization of the process operation. Real Time Optimization (RTO), which is based on an economic criterion, is usually performed in an upper level of the control structure and sends optimizing targets to the lower dynamic control layer where the advanced control drives the system to optimum targets. In this structure, the RTO employs a complex stationary non-linear model of the process for the optimization and the advanced control is usually implemented through a MPC based on a linear model. In this paper, the application of such optimization structure to an industrial Propylene/Propane (PP) splitter is tested in a simulation platform based on the integration of the commercial dynamic simulator Dynsim® and the rigorous steady-state optimizer ROMeo® with real-time facilities of Matlab. The advanced control is represented by an Infinite Horizon Model Predictive controller (IHMPC), based on a space-state model in the incremental form that reproduces the step response model and considers the existence of zone control, optimizing targets for the inputs and can accommodate time delays. In this simulation platform the optimization and advanced control of a Propylene/Propane splitter of an oil refinery is studied. The simulation results show that proposed RTO/advanced control structure is stable and can be implemented in the real system. © IFAC.

关键词： Model predictive control

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Identification experiments for the optimizing control of multiple recycle processes

Identification experiments for the optimizing control of mul...

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10th IFAC symposium on dynamics and control of process systems, DYCOPS 2013

作者： Seki, Hiroya Shamsuzzoha, Mohammad Chemical Resources Laboratory Tokyo Institute of Technology 4259-R1-19 Nagatsuta Midori-ku Yokohama 226-8503 Japan Chemical Engineering Department KFUPM Dhahran 31261 Saudi Arabia

ISBN: (纸本)9783902823595

An identification experiment procedure for the optimizing control of reactor/separator processes with multiple material recycle streams is proposed. Steady state relation between the cost related variables and the operation variables are approximated through response surface models. To minimize the perturbation due to the identification experiments, Latin hypercube design is applied to the selection of the sampling points and their implementation sequence is determined by the application of the traveling salesman problem. The procedure is applied to the simulated HDA (hydrodealkylation of toluene) plant to identify an unconstrained optimal operating condition. © IFAC.

关键词： Traveling salesman problem

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Uneven length batch process monitoring using function space correspondence analysis

Uneven length batch process monitoring using function space ...

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10th IFAC symposium on dynamics and control of process systems, DYCOPS 2013

作者： Ela, Arora Detroja, Ketan P. Dharmsinh Desai University Nadiad Gujarat - 387 001 India Indian Institute of Technology Hyderabad Yeddumailaram Andhra Pradesh - 502205 India

ISBN: (纸本)9783902823595

One most significant challenge in batch process monitoring, compared to continuous process monitoring, is handling three-dimensional historical data for batch processes. Conventional batch process monitoring approaches involve unfolding of such historical data into two dimensions. However, this simple unfolding technique is not applicable if batch duration is not constant. For monitoring of uneven length batch processes, function space analysis based principal component analysis (FSPCA) had been proposed earlier. However, this approach has some limitations because PCA is not effective when it comes to fault diagnosis of highly nonlinear systems. In this paper, a new technique called function space correspondence analysis (FSCA) is proposed for monitoring of uneven length batch processes. The proposed FSCA technique is intended to overcome such limitations and to achieve improved diagnostic performance. The improved performance is due to better discriminatory ability of the CA algorithm. Improved diagnostic capabilities of the proposed FSCA technique is demonstrated using fed batch penicillin cultivation process as a case study. The monitoring results demonstrate improved diagnostic performance with FSCA. © IFAC.

关键词： Principal component analysis

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Dust Explosion Quantitative Risk Management for Nontraditional Dusts

Dust Explosion Quantitative Risk Management for Nontradition...

引用

14th EFCE International Conference on Loss Prevention and Safety Promotion in the process Industries (LP)

作者： Hossain, Md Nur Amyotte, Paul R. Khan, Faisal I. Abuswer, Meftah A. Skjold, Trygve Morrison, Luke S. Dalhousie Univ Engn & Appl Sci Halifax NS Canada Mem Univ St John NF Canada GexCon AS Bergen Norway Loss Control Fredericton NB Canada

ISBN: (纸本)9788895608228

The current paper describes an approach for dust explosion quantitative risk management of the following nontraditional particulate fuel systems: (i) nanomaterials having particles with dimensions between 1 and 100 nm, (ii) flocculent (fibrous) materials characterized by a length-to-diameter ratio rather than a particle diameter, and (iii) hybrid mixtures consisting of a combustible dust and a flammable gas (or a combustible dust wetted with a flammable solvent). Experimental results are considered as input to a quantitative risk management framework so as to provide a comprehensive procedure to analyze, assess and control the likelihood and consequences of explosions of nontraditional dusts. Using concepts drawn from previous studies, the framework consists of three main components: (i) a new combined safety management protocol, (ii) use of the CFD (computational fluid dynamics) software DESC (Dust Explosion Simulation Code) and FTA (Fault Tree Analysis) to determine explosion consequences and likelihood, respectively, and (iii) application of the hierarchy of controls (inherent, engineered and procedural safety) to achieve residual risk reduction.

关键词： Explosions

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Two dimensional recursive least squares for batch processes system identification

Two dimensional recursive least squares for batch processes ...

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10th IFAC symposium on dynamics and control of process systems, DYCOPS 2013

作者： Cao, Zhixing Yang, Yi Lu, Jingyi Gao, Furong Dept. of Chemical and Biomolecular Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Dept. of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (纸本)9783902823595

Recursive system identification is an important problem in many advanced control techniques, such as adaptive control. This paper presents a new approach of two dimensional recursive least squares identification method suitable for batch processes. In this way, system identification is carried out not only using the information from time direction within the batch but also from batch to batch direction. A constraint term is incorporated in the cost function to reduce parameters varying. A guideline for selecting weight matrix in application is also provided. Furthermore, simulation results based on the data obtained from a model of injection moulding, a typical batch process, are illustrated to testify the superiority of the proposed method over the conventional recursive leasts squares. © IFAC.

关键词： Injection molding

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Modeling and control of coal mill

Modeling and control of coal mill

引用

10th IFAC symposium on dynamics and control of process systems, DYCOPS 2013

作者： Pradeebha, P. Pappa, N. Vasanthi, D. Department of Instrumentation Engineering Madras Institute of Technology Anna University India

ISBN: (纸本)9783902823595

The paper presents development and validation of coal mill model (including the action of classifier) to be used for improved coal mill control. The model is developed by using the mass and heat balance equations of the coal mill. Genetic Algorithm is used to estimate the unknown parameters that are used in the model validation. The advantage is that the raw data used in modeling can be obtained without any extensive mill tests. The simulation results show a satisfactory agreement between the model response and measured value. Apart from the conventional PID controller, inorder to ensure tight control with less overshoot and to handle constraints Model Predictive controller is designed to maintain outlet temperature and pulverized coal flow at desired set point value. © IFAC.

关键词： Genetic algorithms

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Multivariate image and texture analysis for film-coated tablets elegance assessment

Multivariate image and texture analysis for film-coated tabl...

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10th IFAC symposium on dynamics and control of process systems, DYCOPS 2013

作者： Ottavian, Matteo Barolo, Massimiliano García-Muñoz, Salvador CAPE-Lab. - Computer-Aided Process Engineering Laboratory Department of Industrial Engineering University of Padova via Marzolo 9 35131 Padova Italy United States

ISBN: (纸本)9783902823595

The use of multivariate image and texture analysis is proposed in this study to quantitatively characterize the elegance of film-coated tablets. Four unsupervised metrics are developed to quantify both the color uniformity of tablet faces/bands and the erosion level inside and outside the tablet logo. Latent variable modeling is used to regress the measured elegance against coating operating conditions in order to investigate the driving forces acting on the system, consistently with the quality-by-design framework promoted by the Food and Drug Administration. © IFAC.

关键词： Image analysis

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Minimum mean squared prediction error criterion based improved independent component analysis method for process monitoring

Minimum mean squared prediction error criterion based improv...

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10th IFAC symposium on dynamics and control of process systems, DYCOPS 2013

作者： Cai, Lianfang Tian, Xuemin Cao, Yuping College of Information and Control Engineering China University of Petroleum Qingdao 266580 China

ISBN: (纸本)9783902823595

Independent component analysis (ICA) is a newly emerging feature extraction method for non-Gaussian process monitoring. However, the extracted feature by ICA may not represent the original process data well, which can result in the degraded monitoring performance. In this paper, an improved ICA method based on the minimum mean squared prediction error criterion is proposed for process monitoring. A new criterion which can make the extracted non-Gaussian feature be efficient representation for the original process data is constructed as the objective function of the improved ICA by integrating the maximum negentropy criterion of the conventional ICA with the minimum mean squared prediction error criterion. Then the gradient ascent algorithm is applied to optimize the constructed objective function for seeking the feature extraction directions. Finally, a monitoring statistic is built based on the extracted feature to detect process faults. The simulation studies on the Tennessee Eastman benchmark process demonstrate that the improve ICA is more effective than the conventional ICA for improving the monitoring performance in terms of the fault detection rate. © IFAC.

关键词： Feature extraction

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