A control-relevant identification strategy for GPC
Authors:
- D.S. ShookDSD.S. Shook
- C. MohtadiCMC. Mohtadi
- S.L. ShahSSS.L. Shah
- 1 July 1992
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Automatic Control
- Vol. 37 (7) , 975-980
Abstract
The question of a suitable control-relevant identification strategy for a class of long-range predictive controllers is addressed. It is shown that under certain conditions the best process model for predictive control is that which is estimated using an identification objective function that is a dual of the control objective function. The resulting nonlinear least squares calculation is asymptotically equal to a standard recursive least squares with an appropriate (model and controller-dependent) FIR data prefilter. Experimental results demonstrate the validity and practicality of the proposed estimation law.Keywords
This publication has 13 references indexed in Scilit:
- Nonminimal predictive controlChemical Engineering Science, 1992
- Identification for long-range predictive controlIEE Proceedings D Control Theory and Applications, 1991
- Model predictive control: Theory and practice—A surveyAutomatica, 1989
- Generalized Predictive Control—Part II Extensions and interpretationsAutomatica, 1987
- Generalized predictive control—Part I. The basic algorithmAutomatica, 1987
- Design variables for bias distribution in transfer function estimationIEEE Transactions on Automatic Control, 1986
- Theory and application of an extended horizon self‐tuning controllerAIChE Journal, 1985
- The internal model principle of control theoryAutomatica, 1976
- On self tuning regulatorsAutomatica, 1973
- Separability, neutrality and certainty equivalence†International Journal of Control, 1971