Abstract
An adaptive control is a technique with strong theoretical background and lots of applications to the abstract and real systems. The big advantage can be found in usability of this control method for systems with negative control properties such as nonlinearity, time-delay, non-minimum behavior etc. The adaptive approach here is based on the choice of the external linear model of the originally nonlinear system parameters of which are updated in defined time moments via recursive identification. The control synthesis employs polynomial approach with linear-quadratic approach and spectral factorization. Resulted controller has two weighting factors as tuning parameters. This paper explores the effect these factors to the control. All proposed approaches were tested by simulations on the mathematical model of the continuous stirred-tank reactor as a typical member of the nonlinear lumped-parameters systems.
This is a preview of subscription content, log in via an institution to check access.
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
Åström, K.J., Wittenmark, B.: Adaptive Control. Addison Wesley, Reading (1989) ISBN 0-201-09720-6
Bobal, V., Böhm, J., Fessl, J., Machacek, J.: Digital Self-tuning Controllers: Algorithms. Implementation and Applications. In: Advanced Textbooks in Control and Signal Processing. Springer-Verlag London Limited (2005) ISBN 1-85233-980-2
Middleton, H., Goodwin, G.C.: Digital Control and Estimation - A Unified Approach. Prentice Hall, Englewood Cliffs (2004) ISBN 0-13-211798-3
Kucera, V.: Diophantine equations in control – A survey. Automatica 29, 1361–1375 (1993)
Ingham, J., Dunn, I.J., Heinzle, E., Prenosil, J.E.: Chemical Engineering Dynamics. An Introduction to Modeling and Computer Simulation, 2nd Completely Revised edn. VCH Verlagsgesellshaft, Weinheim (2000) ISBN 3-527-29776- 6
Stericker, D.L., Sinha, N.K.: Identification of continuous-time systems from samples of input-output data using the δ-operator. Control-Theory and Advanced Technology 9, 113–125 (1993)
Hunt, K.J., Kucera, V., Sebek, M.: Optimal regulation using measurement feedback. A polynomial approach. IEEE Transactions on Automation Control 37(5), 682–685 (1992)
Zelinka, I., Vojtesek, J., Oplatkova, Z.: Simulation Study of the CSTR Reactor for Control Purposes. In: Proc. of 20th European Conference on Modelling and Simulation, ESCM 2006, Bonn, Germany, pp. 479–482 (2006)
Rao, G.P., Unbehauen, H.: Identification of continuous-time systems. IEEE Process-Control Theory Application 152, 185–220 (2005)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this paper
Cite this paper
Vojtesek, J., Dostal, P. (2013). Effect of Weighting Factors in Adaptive LQ Control. In: Zelinka, I., Chen, G., Rössler, O., Snasel, V., Abraham, A. (eds) Nostradamus 2013: Prediction, Modeling and Analysis of Complex Systems. Advances in Intelligent Systems and Computing, vol 210. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00542-3_27
Download citation
DOI: https://doi.org/10.1007/978-3-319-00542-3_27
Publisher Name: Springer, Heidelberg
Print ISBN: 978-3-319-00541-6
Online ISBN: 978-3-319-00542-3
eBook Packages: EngineeringEngineering (R0)