Process Control and Optimization Consortium

 Updated: 06/27/05 06:19 PM     

 

 A Multi-Scale Model Predictive Control Strategy 

Authors:

Arun Krishnan¹ and Karlene A. Hoo*
¹ 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

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