检索结果-内蒙古大学图书馆

The Effect of controllers in State Estimation Schemes

IFAC Proceedings Volumes 1998年第11期31卷 577-582页

作者： Guillermo E. Eliçabe Christos Georgakis Departamento de Ingeniería Química/INTEMA Facultad de Ingeniería Universidad Nacional de Mar del Plata (7600) Mar del Plata Argentina Chemical Process Modeling and Control Research Center Lehigh University Iacocca Hall #111 Bethlehem PA 18015 USA

It is common practice in state estimation of chemical systems to include augmented states modeled as random constant or random walk processes. When in these systems, process controllers with integral term are present, undesirable interaction effects may occur between the augmented states and the controllers. It was noted in practice that if no attention is paid to this interaction the resulting estimator may diverge. In this work the interaction between controller and augmented states is analyzed. Using linear systems theory, it is shown that the unwanted interaction and final divergence are caused by lack of observability at steady state and consequently a test to check observability at steady state is developed. In many cases the test can be performed by simple inspection. When this is not the case, results can be obtained after a few manipulations. A series of examples are given where the concept of observability at steady state is applied to help detecting and preventing the negative interaction between controllers and augmented states. Finally, a discussion is presented comparing the results of the standard observability test, applied to a real problem, with those obtained with the test developed here and with the behavior of a real estimator for the same problem. It is concluded that the standard observability test is not able to discriminate between different estimator designs and consequently to produce practical results as those obtained with the alternative test, i.e. the detection of unfeasible estimator designs.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Identification of reduced order average linear models from nonlinear dynamic simulations

Identification of reduced order average linear models from n...

引用

American control Conference (ACC)

作者： W.A. Docter C. Georgakis Chemical Process Modeling and Control Research Center Department of Chemical Engineering Lehigh University Bethlehem PA USA

Presents a general methodology for the identification of average linear low order models (ALLOM) from data collected from detailed nonlinear models. While there are many methods available in the literature for identifying linear models, these methods tend to produce inaccurate and ill-conditioned models when used on nonlinear data sets. The method in this paper differs from traditional linearization methods in that it better approximates the dynamic characteristics over a wider area around the reference steady state.

关键词： Signal processing Predictive models Open loop systems chemical processes process control chemical engineering Steady-state Separation processes Thermodynamics State estimation

来源：评论

学校读者我要写书评

暂无评论

Closed-Loop Identification of State Space Models using Subspace Techniques

引用

IFAC Proceedings Volumes 1997年第9期30卷 37-42页

作者： Hemant Jha Christos Georgakis Chemical Process Modeling and Control Research Center and Department of Chemical Engineering Lehigh University Bethlehem Pennsylvania 18015 Phone: (610)-758-5432 Fax:(610)-758-5297

The paper presents a subspace algorithm which identifies the process model from closed-loop data. The algorithm is based on the use of a closed-loop oblique projection for the direct identification of the plant dynamics. This closed-loop oblique projection is particularly useful because it eliminates the use of a minimal realization step after the identification has been performed. Similar to the open-loop algorithm, the proposed closed-loop algorithm is ideally suited for MIMO problems.

关键词： Closed-loop Identification Subspace Methods State Space Models Multivariable Systems Matrix Projection

来源：评论

学校读者我要写书评

暂无评论

Real-time estimation and control of particle size in semi-batch emulsion polymerization

Real-time estimation and control of particle size in semi-ba...

引用

American control Conference (ACC)

作者： V. Liotta C. Georgakis M.S. El-Aasser Air Products and Chemicals Inc. Allentown PA USA Chemical Process Modeling and Control Research Center and Emulsion Polymers Institute Lehigh University Bethlehem PA USA

The control of the relative particle growth of a bidisperse emulsion polymerization is investigated in an automated reactor control facility capable of online density and online particle size measurements. Final diameter ratio values are controlled by manipulating the monomer feed rate to the reactor using a control scheme comprised of a parameter adaptive Kalman filter with steady state gains and a nonlinear model predictive controller. One of the main features of the implemented controller is the connection of the prediction horizon to the criterion that the overall conversion equal 90% at the end of the batch. Feedback is incorporated into the algorithm at each sampling time by starting the model prediction calculation at the current estimated values of the model states. The controller performs well to meet a challenging diameter ratio set point at the end of the batch. The robustness of the controller to reject an induced initial initiator concentration disturbance is demonstrated.

关键词： Size control Automatic control Predictive models Inductors Polymers Size measurement Feeds Programmable control Adaptive control Steady-state

来源：评论

学校读者我要写书评

暂无评论

Reference system based model predictive control

引用

IFAC Proceedings Volumes 1996年第1期29卷 5923-5928页

作者： Lokesh Kalra Chriatos Georgakis Chemical Process Modeling and Control Research Center and Department of Chemical Engineering Lehigh University Bethlehem Pennsylvania USA

Despite recent advances in the field, the tuning of presently popular Model Predictive control formulations is largely a trial and error procedure. Motivated by this fact, a Reference System based tuning is explored through Reference System Model Predictive control. The RS-MPC algorithm is examined because of its potentially more intuitive approach to tuning. Under this methodology the tuning involves the selection of two parameters for each controlled variable. The first parameter adjusts the shape of the response and the second one affects the speed. Using these, instead of the weight-based tuning of conventional MPC, much of the trial and error is eliminated. The most important features of the controller arc elucidated through the performance of the STSO and MIMO cases for the Amoco Fluid Catalytic Cracker process simulation.

关键词： Multivariable Feedback control Predictive control Models Tuning Characteristics control Algorithms Simulators

来源：评论

学校读者我要写书评

暂无评论

Decentralized PCA Charts for Performance Assessment of Plant-Wide control Structures

引用

IFAC Proceedings Volumes 1996年第1期29卷 5894-5898页

作者： Christos Georgakis Bethany Steadman Vincenzo Liotta Chemical Process Modeling and Control Research Center and Department of Chemical Engineering Lehigh University Bethlehem Pennsylvania USA

Static principal component analysis (PCA) statistical charts are used to assess and compare the performance of two plant-wide control strategies of the Tennessee Eastman process. Both centralized and decentralized charts are used as well as charts relating to the energy and material balance of the process. In most cases these charts reveal the origin of the disturbance and the effectiveness of the control structure to compensate for the disturbance. Differences and similarities between the two control structures are also examined.

关键词： process control large scale systems multivariable feedback systems multivariable quality control control schemes disturbance localization disturbance rejection

来源：评论

学校读者我要写书评

暂无评论

Wavelet techniques in the compression of process data

Wavelet techniques in the compression of process data

引用

American control Conference (ACC)

作者： M.J. Watson A. Liakopoulos D. Brzakovic C. Georgakis Chemical Process Modeling and Control Research Center Lehigh University USA Chemical Process Modeling and Control Research Center Lehigh University Bethlehem PA USA

The objective of this paper is to explore the application of wavelets to the field of data compression in the process industry. The wavelet transform is compared with the discrete Fourier and cosine transforms. To examine a complete approach to data compression, quantization techniques are applied to the transformed coefficients. Different quantiser designs are used for the compression of data from an industrial distillation column. Comparisons are made with the Box-Car and backward-slope methods currently used in the process industries.

关键词： Data compression Discrete wavelet transforms Quantization chemical processes process control chemical industry Industrial control Discrete Fourier transforms Fourier transforms Frequency

来源：评论

学校读者我要写书评

暂无评论

Disturbance detection and isolation by dynamic principal component analysis

Disturbance detection and isolation by dynamic principal com...

引用

作者： Ku, Wenfu Storer, Robert H. Georgakis, Christos Chemical Process Modeling and Control Research Center Iacocca Hall Lehigh University 111 Research Dr. Bethlehem PA 18015 United States Department of Chemical Engineering Department of Industrial Engineering

In this paper we extend previous work by ourselves and other researchers in the use of principal component analysis (PCA) for statistical process control in chemical processes. PCA has been used by several authors to develop techniques to monitor chemical processes and detect the presence of disturbances [1-5]. In past work, we have developed methods which not only detect disturbances, but isolate the sources of the disturbances [4]. The approach was based on static PCA models, T2 and Q charts [6], and a model bank of possible disturbances. In this paper we use a well-known 'time lag shift' method to include dynamic behavior in the PCA model. The proposed dynamic PCA model development procedure is desirable due to its simplicity of construction, and is not meant to replace the many well-known and more elegant procedures used in model identification. While dynamic linear model identification, and time lag shift are well known methods in model building, this is the first application we are aware of in the area of statistical process monitoring. Extensive testing on the Tennessee Eastman process simulation [7] demonstrates the effectiveness of the proposed methodology.

关键词： Principal component analysis

来源：评论

学校读者我要写书评

暂无评论

Studies in plant-wide controllability using the Tennessee Eastman Challenge problem, the case for multivariable control

Studies in plant-wide controllability using the Tennessee Ea...

引用

American control Conference (ACC)

作者： D.R. Vinson C. Georgakis J. Fossy Air Products and Chemicals Inc. Allentown PA USA Chemical Process Modeling and Control Research Center and Department of Chemical Engineering Lehigh University Bethlehem PA USA

The design and application of a new control structure for the Tennessee Eastman Challenge process is presented. This structure is primarily single-input single-output (SISO) but it has been augmented with the concept of extensive variable control to intuitively design multivariable structures for the regulation of the production rate and the product purities. A review of plant-wide control methodologies is provided to lay the basis for a discussion of SISO versus multivariable approaches.

关键词： controllability Computer aided software engineering control systems process design chemical products chemical processes process control Steady-state Recycling Production systems

来源：评论

学校读者我要写书评

暂无评论

Bilinear Identification of Nonlinear processes

引用

IFAC Proceedings Volumes 1994年第2期27卷 47-52页

作者： James F. Bartee Christos Georgakis Chemical Process Modeling and Control Research Center Department of Chemical Engineering Lehigh University Bethlehem Pennsylvania USA 18015 Fax: (610)758-5432 Internet

Identification of nonlinear processes using bilinear models is presented. To avoid direct estimation of the bilinear model parameters, a dynamically equivalent input/output model structure is developed through an analysis of the observability of the bilinear system. Calculation of the Volterra kernels from the input/output model parameters is presented and the overparameterization of the input/output model form is examined by comparison with the Volterra series model form. Constraint equations calculated from this guarantees the dynamic equivalence of the input/output and state-space forms. The input/output model parameters are estimated through an extended least-squares method. An example of a fluid catalytic cracking unit (FCCU) is presented.

关键词： Nonlinear Identification Bilinear Models Input/Output Models Volterra Kernels FCCU

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：