On-line tuning strategy for model predictive controllers
| Autor: | Evanghelos Zafiriou, Ashraf Al-Ghazzawi, Adnan Nouh, Emad Ali |
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| Rok vydání: | 2001 |
| Předmět: |
Engineering
Mathematical optimization Optimization problem business.industry Linear model Continuous stirred-tank reactor Industrial and Manufacturing Engineering Computer Science Applications Model predictive control Control and Systems Engineering Control theory Fractionating column Modeling and Simulation Line (geometry) Sensitivity (control systems) Linear approximation business |
| Zdroj: | Journal of Process Control. 11:265-284 |
| ISSN: | 0959-1524 |
| DOI: | 10.1016/s0959-1524(00)00033-0 |
| Popis: | This paper presents an intuitive on-line tuning strategy for linear Model Predictive Control (MPC) algorithms. The tuning strategy is based on the linear approximation between the closed-loop predicted output and the MPC tuning parameters. By direct utilization of the sensitivity expressions for the closed-loop response with respect to the MPC tuning parameters, new values of the tuning parameters can be found to steer the MPC feedback response inside predefined time-domain performance specifications. Hence, the algorithm is cast as a simple constrained least squares optimization problem which has a straightforward solution. The simplicity of this strategy makes it more practical for on-line implementation. Effectiveness of the proposed strategy is tested on two simulated examples. One is a linear model for a three-product distillation column and the second is a non-linear model for a CSTR. The effectiveness of the proposed tuning method is compared to an exiting offline tuning method and showed superior performance. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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