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2008 American control Conference (ACC), vol.4

作者： Pradeep Y. Tiwari Mayuresh V. Kothare Chemical Process Modeling and Control Center Department of Chemical Engineering Lehigh University Bethlehem PA USA

Repetitive systems can be characterized by two time variables, namely, the finite time within each repeating cycle and the cycle index, each embodying a distinct connotation of time. Conventional optimal control theory does not explicitly account for this two dimensional (2D) description of repetitive systems. We propose a new formulation for control of repetitive systems using Model Predictive control (MPC) that explicitly incorporates a 2D representation of the system. The proposed formulation uses a 2D Lyapunov function and the stability requirements are established along each time dimension of the system. The resulting controller synthesis problem is expressed in convex form using Linear Matrix Inequalities (LMIs). The approach allows explicit incorporation of input/output constraints in the controller design. Two examples illustrate the applicability of the proposed approach.

关键词： Predictive models Predictive control Linear matrix inequalities Radio control control systems control system synthesis Stability Economic forecasting chemical processes chemical industry

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The Impact of process Diversity on Distillation Column control

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IFAC Proceedings Volumes 1989年第8期22卷 1-7页

作者： W.L. Luyben Process Modeling and Control Center Department of Chemical Engineering Lehigh University 111 Research Drive Bethlehem PA 18015 USA

The engineering science of distillation column design and control is considered by many academic visionaries to be a mature field that is not worthy of continued research. However, the economic importance of distillation in the chemical and petroleum industries continues to be very significant. This is true in both old and new plants and processes. The replacement of "inefficient" distillation by newer separation methods that has been predicted for over a decade has not occurred. The hard-nosed economics continue to show well-designed distillation systems can out-perform any of the alternatives in a very large number of processes. Many universities around the world with more practical engineering research interests continue to have active research programs in distillation. This is particularly true in the area of the dynamics and control of distillation systems. The increasing diversity and complexity of distillation systems present significant design and control challenges for future engineers. This paper attempts to point out how the extensive diversity that is encountered in distillation applications has a significant impact on the design of control systems for distillation.

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The Value of Simple Multivariable and Nonlinear Models in process control

The Value of Simple Multivariable and Nonlinear Models in Pr...

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American control Conference (ACC)

作者： Christos Georgakis Department of Chemical Engineering and Chemical Process Modeling and Control Research Center Lehigh University Bethlehem PA USA

Simple conceptual or mathematical models have always been used in design of linear SISO process controllers. On the other hand the design of nonlinear or MIMO controllers has always been perceived as requiring a detailed dynamic model. This communication aims to show that, the use of simple models, can drastically affect the design of such controllers by suggesting a design framework that centers around the extensive variable of the process instead of the intensive one that are usually measured.

关键词： process control Mathematical model Inductors chemical processes Communication system control Polyethylene chemical reactors Polymers Tellurium chemical engineering

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Nonlinear model predictive control of end-use properties in batch reactors under uncertainty

Nonlinear model predictive control of end-use properties in ...

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European control Conference (ECC)

作者： Jaleel Valappil Christos Georgakis Chemical Process Modeling and Control Research Center and Department of Chemical Engineering Lehigh Univeristy Bethlehem PA USA

There are significant incentives in controlling the end-use properties in batch reactors to reduce the variability in the final product quality specifications. Here we define an approach for controlling the properties within a desired target region, instead of a set point, with an economic objective and with consideration of the model uncertainty. The approach to handling process-model mismatch is based on determining the uncertainty in the predicted final values of the properties, in the form of elliptical confidence regions. The controller then ensures that the complete confidence region is within the target set. A semi-infinite programming problem is solved to find the input values for the rest of the batch, utilizing techniques that reduce the complexity of the problem. An emulsion polymerization process for styrene is chosen as a case study and the methods developed here are demonstrated on this challenging example process.

关键词： Uncertainty Approximation methods Mathematical model Covariance matrices Equations Programming Eigenvalues and eigenfunctions

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On-line Estimation of Reaction Rates in Batch Reactors

On-line Estimation of Reaction Rates in Batch Reactors

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American control Conference (ACC)

作者： Guillermo Elicabe Christos Georgakis Chemical Process Modeling and Control Research Center Department of Chemical Engineering Lehigh University Bethlehem PA USA

Very often one needs to know the current values of reaction rates in chemical reactors in order to control them effectively or in order to avoid unsafe operating conditions. ln this work state estimation techniques are used to estimate on-line reaction rates in well mixed isothermal batch reactors. The proposed scheme assumes the availability of on-line measurements of overall concentrations of the reactants, and the lack of knowledge on the reaction rate dependence with those concentrations. The state estimator used in this application is a Kalman filter based estimator. Relationships between the continuous and the discrete versions of the filter as well as a Laplace domain analysis were considered. The estimation scheme is applied to two examples of semi-continuous emulsion co-polymerization.

关键词： Inductors Equations chemical reactors Tellurium State estimation Content addressable storage Isothermal processes Kalman filters Phase estimation Steady-state

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Identification of reduced order average linear models from nonlinear dynamic simulations

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

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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

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Nonlinear control Structures for chemical Reactors

Nonlinear Control Structures for Chemical Reactors

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American control Conference (ACC)

作者： R. Donald Bartusiak Christos Georgakis Matthew J. Reilly Chemical Process Modeling and Control Research Center Department of Chemical Engineering Lehigh University Bethlehem PA USA

A nonlinear feedback controller for chemical reaction dynamic systems is examined in which the control action is a function of the deviation of the reaction rate from steady state. The motivations for this controller are (i) the finding that the reaction rate sensitivity to composition and temperature deviations is closely associated with the slow or unstable dynamic modes for the reaction systems studied to date; (ii) the controller nonlinearity mirrors the principal process nonlinearity; and (iii) such a control law is intuitively meaningful. In this paper, we develop the controller and propose a nonlinear analysis method for an idealized model of the continuous stirred tank reactor.

关键词： chemical reactors Temperature control Nonlinear control systems Steady-state chemical engineering Open loop systems Temperature sensors Continuous-stirred tank reactor Inductors Temperature distribution

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State estimation and nonlinear model predictive control of end-use properties in batch reactors

State estimation and nonlinear model predictive control of e...

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American control Conference (ACC)

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

There are economic incentives in controlling the end-use properties in batch reactors to reduce the variability in the final product quality specifications. Here we define an approach for controlling the properties within a desired target region, instead of a set point, with an economic objective and with consideration of the model uncertainty. The approach to handling process-model mismatch is based on determining the uncertainty in the predicted final values of the properties, in the form of elliptical confidence regions. The controller then ensures that the complete confidence region is within the target region. A semi-infinite programming problem is solved to find the input values for the rest of the batch. The methods developed here are demonstrated on an emulsion polymerization example.

关键词： State estimation Predictive models Predictive control Inductors Uncertainty Economic forecasting Polymers chemical processes process control chemical engineering

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Bilinear Identification of Nonlinear processes

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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

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Optimal parameter estimation of the Izhikevich single neuron model using experimental Inter-Spike Interval (ISI) data

Optimal parameter estimation of the Izhikevich single neuron...

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作者： Kumar, Gautam Aggarwal, Vikram Thakor, Nitish V. Schieber, Marc H. Kothare, Mayuresh V. Department of Chemical Engineering Chemical Process Modeling and Control Center Lehigh University Bethlehem PA 18015 United States Department of Biomedical Engineering Johns Hopkins University Baltimore MD 21205 United States Department of Neurobiology and Anatomy University of Rochester Medical Center Rochester NY 14627 United States

ISBN: (纸本)9781424474264

We propose to use the Izhikevich single neuron model to represent a motor cortex neuron for studying a control-theoretic perspective of a neuroprosthetic system. The problem of estimating model parameters is addressed when the only available data from intracortical recordings of a neuron are the Inter-Spike Intervals (ISIs). Non-linear constrained and unconstrained optimization problems are formulated to estimate model parameters as well as synaptic inputs using ISIs data. The primal-dual interior-point method is implemented to solve the constrained optimization problem. Reasonable model parameters are estimated by solving these optimization problems which may serve as a template for studying and developing a model of ensemble cortical neurons for neuroprosthesis applications. © 2010 AACC.

关键词： Neurons

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