Batch Systems

A Multi-Scale Model Predictive Control Strategy

Authors: Arun Krishnan† and Karlene A. Hoo*
GSE Systems, Maryland
* Department of Chemical Engineering, Texas Tech University

ABSTRACT

Multi-scale systems defined on trees can provide local time and scale information about the behavior of the process in contrast to the usual time-domain model and Fourier transforms. Since the model predictive control (MPC) framework uses a model of the process to determine the optimal control action, improving the model by using a multi-scale approach will result in controller actions that can compensate for phenomena that may occur at different scales. This work develops multi-scale models on trees, describes how these time-scale models can be used in the MPC framework to represent both the process and the disturbance, and proposes a new optimization strategy to determine the controller actions such that the optimal inputs, at the finer scales reflect the inputs at the coarser scales. The performance of this multi-scale MPC strategy is demonstrated on a continuous process and on a chemical batch reactor.

 

Publication Information: Industrial & Engineering Chemistry Research, Vol. 38, pp 1973-1986, 1999.

Corresponding Author: Karlene A. Hoo

 

Batch Reactor Control Using a Multiple Model-based Controller Design

Authors: Arun Krishnan† and Karlene A. Hoo*
University of South Carolina, Columbia, SC
* Department of Chemical Engineering, Texas Tech University

ABSTRACT

This work presents the development of a model-based controller design called Multiple Model Predictive Control (MMPC) based on a set of linear, time-varying, state space models to regulate batch processes according to multiple, pre-specified reference profiles. Sufficient conditions for stability and boundedness of the dynamic evolution of the forced nonlinear system are provided. The performance of the MMPC design is demonstrated on a model of a batch reactor that represents the production of a polymer product.

 

Publication Information: The Canadian Journal of Chemical Engineering, Vol. 76, 1998.

Corresponding Author: Karlene A. Hoo