Transistion Control

AIChE 2002 Presentation: Model Predictive Control Applied to Transition Control

 

Multiple Model Adaptive Control Design for a MIMO Chemical Reactor

Authors: Ramakrishnan Gundala† and K. A. Hoo*
† Department of Chemical Engineering, University of South Carolina
* Department of Chemical Engineering, Texas Tech University

ABSTRACT

Multiple adaptive and nonadaptive models are used to represent the behavior of processes that are known to transition to unknown regimes in the operating space. The adaptive models investigated are of two types, free-running and re-initializable, that differ in the initialization of their parameters. Using these models and their companion controllers in a model reference adaptive structure, it is shown that this mixed model set can provide satisfactory control of a nonlinear, interactive, multiple-input multiple-output chemical reactor with active constraints.

 

Publication Information: Industrial & Engineering Chemistry Research, Vol. 39, pp 1554-1563, 2000.

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Corresponding Author: Karlene A. Hoo

 

Dynamic Transition Control Structure for a Class of SISO Nonlinear Systems

Authors: Debin Sun† and Karlene A. Hoo*
† Alcatel, Inc. Toronto, Canada
* Department of Chemical Engineering, Texas Tech University

ABSTRACT

Most chemical processes are nonlinear in nature and large set point changes or load disturbances make such processes more challenging for control. Recently a simple transition control structure was introduced so that the trade-off between nominal performance and robust stability of the model with large uncertainties is converted into the development of several models with small uncertainties in such a way that the former problem can be solved satisfactorily. In this work, a modification to that transition control structure is proposed to address nonlinear systems. The performance of this transition control structure is demonstrated on a nonlinear pH neutralization process. The simulation results show that the proposed structure has good properties not only for set point changes but also for disturbance rejection.

 

Publication Information: IEEE Trans. on Cont. Sys. Tech., Vol. 7, pp 622--629, 1999.

Corresponding Author: Karlene A. Hoo

 

Transition Control Using Multiple Adaptive Models and an H-infinity Controller Design

Authors: Zhenhua Tian, Karlene A. Hoo*
* Department of Chemical Engineering, Texas Tech University

ABSTRACT

By transition control, it is meant a type of control method that is employed when the plant transitions from one operating state to another as a result of a set point change or a disturbance. This paper develops an adaptive multiple model approach that simultaneously adapts the model parameters and the parameters of an H-infinity controller design. The method is then demonstrated on a nonlinear chemical reactor that transitions between two stable operating states.

 

Publication Information: Proceedings of 2001 American Automatic Control Conference, Anchorage, AK

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Corresponding Author: Karlene A. Hoo

 

Nonlinear Adaptive Control with Parameter Estimation of a CSTR

Authors: Karlene A. Hoo*, Michael J. Piovoso†, Vadim Rokhlenko‡ and Allon Guez±
* Department of Chemical Engineering, University of South Carolina
† E. I. Dupont de Nemours & Co, Wilmington, DE 19898, USA
‡ Drexel University, Electrical and Computer Engineering Department, Philadelphia, PA 19104, USA

ABSTRACT

The goal of this paper is to describe a linearizing feedback adaptive control structure which guarantees high quality regulation of the output error in the face of unknown parameters. The effectiveness of this control structure is demonstrated on a continuous stirred tank reactor in two instances. The first is when there is full state feedback and the second when only temperature measurements are available. In the latter a nonlinear observer is constructed to infer conversion. In both cases conditions for asymptotic stability are presented and discussed.

 

Publication Information: J. Process Control, Vol.5 , No.3, pp 137-148, 1995

Corresponding Author: Karlene A. Hoo

 

Operating Regime-Based Controller Strategy for Multi-Product Processes

Authors: Karlene A. Hoo*, James G. Charboneau*, and Michael J. Piovoso†
* Department of Chemical Engineering, University of South Carolina
 † Dupont Chemical Company, Wilmington, DE

ABSTRACT

A hybrid, dynamical supervisory control strategy is introduced to control multi-product processes. The scheme involves the selection of the best setpoint controller, from an existing family of feedback controllers, to be placed into feedback with the process so as to cause the output to track the desired setpoint. This task is performed without exhaustive trial and error, by minimizing a specific normed output estimation error that relates the process output to a shared controller state. The perfornlance of the supervisory control strategy is demonstrated on a continuous-stirred tank reactor that can be operated at three different conversion levels. However, the most desirable operating point is open-loop unstable. Linear controllers are designed for each operating region and the role of the supervisory control strategy will be to determine the switching logic as different scheduling policies are demanded.

 

Publication Information: J. Process Control, Vol.7 , No.1, pp 41-56, 1997

Corresponding Author: Karlene A. Hoo

 

Transition Control Using a State-Shared Model Approach

Authors: Zhenhua Tian and Karlene A. Hoo*
* Department of Chemical Engineering, Texas Tech University

ABSTRACT

Transition control is defined in this work as a type of control method that is employed when the plant transitions from one steady state to another as a result of a set point change. Recent approaches have relied on multiple models and centralized or decentralized controller designs to address this issue. This work introduces and develops a transition control framework that consists of multiple fixed and adaptive models within a state-shared non-minimal realization and an H-infinity controller design. The efficacy of this transition control framework is demonstrated on two nonlinear single-input single-output reactors in the face of modeling errors, parameter uncertainties and disturbances.

 

Publication Information: Computers and Chemical Engineering, Vol. 27(11), pp 1641-1656, 2003.

Corresponding Author: Karlene A. Hoo

 

State-Shared Model For Multi-Input Multi-Output Systems

Authors: Zhenhua Tian and Karlene A. Hoo*
* Department of Chemical Engineering, Texas Tech University

ABSTRACT

This work proposes a method to construct a state-shared model for multiple-input multiple-output (MIMO) systems. A state-shared model is defined as a linear time invariant state-space structure that is driven by measurement signals - the plant outputs and the manipulated variables, but shared by different multiple input/output models. The genesis of the state-shared model is based on a particular reduced non-minimal realization. Any such realization necessarily fulfills the requirement that the output of the state-shared model be an asymptotically correct estimate of the output of the plant, if the process model was selected appropriately. The approach is demonstrated on a nonlinear MIMO system -- a physiological model of calcium fluxes that controls muscle contraction and relaxation in human cardiac myocytes.

 

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Corresponding Author: Karlene A. Hoo

 

Multi-Model Based Control of the Tennessee Eastman Process

Authors: Zhenhua Tian and Karlene A. Hoo*
* Department of Chemical Engineering, Texas Tech University

ABSTRACT

This work addresses the model-based control of the Tennessee Eastman (TE) challenge problem using a state-shared model. A detailed mechanistic nonlinear model is developed and validatedwith data taken from the original Downs and Vogel work and their accompanying Fortran programs. Two model predictive plantwide control strategies that differ in the type of models used are applied to address regulation and transition control. The first employs multiple fixed parameter models, identified at the known grades and the second uses an adaptive state-shared modelconstructed from three fixed parameter models and one specialized adaptive model. The first MPC strategy demonstrates closed-loop regulation and grade transition performance especially when the the worst disturbance, the loss of the A feed is present. The second MPC strategy provides better closed-loop performance for grade transitions when compared with the first MPC strategy.

 

Publication Information: Industrial & Engineering Chemistry Research, Vol. 44(9), pp 3187-3202, 2005

Corresponding Author: Karlene A. Hoo