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Improving the Performance of a Chemical Plant Using Nonlinear Model Predictive Control (NMPC) Techniques
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 37 - Number 11 |
| Year of Publication: 2012 |
| Authors: Bahman Pirayesh, Dr. H. Jazayeri-Rad |
10.5120/4734-6929
|
Bahman Pirayesh, Dr. H. Jazayeri-Rad . Improving the Performance of a Chemical Plant Using Nonlinear Model Predictive Control (NMPC) Techniques. International Journal of Computer Applications. 37, 11 ( January 2012), 47-60. DOI=10.5120/4734-6929
Abstract
The key objective of NMPC is to find the best vector of control functions that minimize or maximize a performance index depending on a given process model (usually a nonlinear differential equation system) as equality constraints, and boundary conditions as inequality constraints on the states and controls. The use of process optimization in the control of chemical reactors presents a useful tool for operating chemical reactors efficiently and optimally. Since batch reactors are generally applied to produce a wide variety of specialty products, there is a great deal of interest to enhance batch operation to achieve high quality and purity product while minimizing the conversion of undesired by-product. In this work, we consider a reactor system which consist of a batch reactor and jacket cooling system as a case study. Two different types of optimization problems, namely, maximum conversion and minimum time problems are formulated and solved and optimal operation policies in terms of reactor temperature or coolant flow rate are obtained. A path constraint such as on the reactor temperature is imposed for safe reactor operation and to minimize environmental impact. Here we employ the method of collocation on finite elements for discretizing the dynamic optimization problem. The numerical solution framework is implemented in MATLAB environment.
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