Abstract
Predictive control is a sort of advanced control strategy, therefore, the study on diagnosis technology of predictive control performance model has both important theoretical and applicable value for maintaining and increasing predictive controller performance, enhancing the promotion and application of advanced control strategy.This paper mainly introduces the predictive controller performance diagnosis methods based on data, and on this basis, puts forward a kind of based on the performance assessment method of PCA similar factor’s predictive control model. The method by introducing performance characteristics subspace to describe the characteristics of each performance type calculates real time data and PCA similar factor among performance subspace of various data, using classification analysis and taking PCA similar factor as measurement merit determines the type in accordance with diagnosis data and locates the reason that causes the performance reduction of predictive control model. And the paper puts forward the performance assessment method that takes advantage of PSO to gain PCA similar factor parameter, and uses simulation results to test the effectiveness of the method.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Maciejowski, J.M.: Predictive Control with Constraints. Prentice Hall, Harlow (2002)
Zhang, Q., Li, S.: Performance monitoring and diagnosis of multivarable modei predictive control using statistical analysis. Chinese Journal of Chemical Engineering 14(2), 207–215 (2006)
Alghazzawi, A., Lennox, B.: Model predicitive control monitoring using multivariate statistics. Journal of Process Control 19(2), 314–327 (2009)
Patwardhan, R.S., Shah, S.L.: Assessing the performance of model predictive controller. Canadian Journal of Chemical Engineer. 80(5), 954–966 (2002)
Schafer, J., Cinar, A.: Multivariable MPC system performance assessment, monitoring and diagnosis. Journal of Process Control 14(2), 113–129 (2004)
Loquasto, F., Seborg, D.E.: Model predictive controller monitoring based on pattern classification and PCA. In: American Control Conference, vol. 3, pp. 1968–1973 (2003)
Loquasto, F., Seborg, D.E.: Monitoring model predictive control systems using pattern classification and neural networks. Industrial Engineering Chemical Research 42, 4689–4701 (2003)
Wise, B.M., Gallagher, N.B.: The process chemometrics approach to process monitoring and fault detection. Journal Process Control 6(6), 329–348 (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
He, D., Shao, S., Yang, P., Zhang, S. (2012). Research on Diagnosis Method of Predictive Control Performance Model Based on Data. In: Wang, J., Yen, G.G., Polycarpou, M.M. (eds) Advances in Neural Networks – ISNN 2012. ISNN 2012. Lecture Notes in Computer Science, vol 7368. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31362-2_52
Download citation
DOI: https://doi.org/10.1007/978-3-642-31362-2_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31361-5
Online ISBN: 978-3-642-31362-2
eBook Packages: Computer ScienceComputer Science (R0)