Abstract
In this chapter the importance of parameter estimation in model development is illustrated through various applications related to reaction systems. In particular, rate constants in a reaction system are obtained through parameter estimation methods. These approaches often require the application of optimisation techniques coupled with dynamic solution of the underlying model.
Linear and nonlinear approaches to parameter estimation are investigated. There is also the application of maximum likelihood principles in the estimation of parameters, as well as the use of orthogonal collocation to generate a set of algebraic equations as the basis for parameter estimation.These approaches are illustrated using estimations of kinetic constants from reaction system models.
| Original language | English |
|---|---|
| Title of host publication | Product and Process Modelling : A Case Study Approach |
| Editors | Ian Cameron, Rafiqul Gani |
| Number of pages | 557 |
| Volume | 11 |
| Publisher | Elsevier |
| Publication date | 2011 |
| Pages | 337-362 |
| ISBN (Print) | 978-0-444-53161-2 |
| Publication status | Published - 2011 |
Keywords
- Reaction systems
- Orthogonal collocation
- Kinetics
- Langmuir-Hinshelwood
- Parameter estimation
- Simulated data
- Measured data
- Maximum likelihood principle
- Optimisation