Enhanced Model Reference Adaptive Control Using Smith Predictor

Article Preview

Abstract:

The main aim of a control system is to repress the instabilities caused by nonlinearities of the system. Dead time is considered to be one of the most significant nonlinearities of a system. Dead time compensators play a vital role in reducing the dead time effects on the processes only to a minute extent. This paper proposes a method to overcome this problem by using Enhanced Model Reference Adaptive Control (MRAC) incorporating Smith Predictor. MRAC belongs to class of adaptive servo system in which desired performance is expressed with the help of a reference model. Enhanced MRAC consists of a fuzzy logic controller which provides adaptation gain to MRAC without human interference. A dead time compensator incorporated in the enhanced MRAC solves the problem of instabilities caused by dead time to a greater extent.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

363-368

Citation:

Online since:

August 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] I. J Nagarath and M Gopal: Control Systems Engineering, New age International Publishers (2007).

Google Scholar

[2] Karl. J. Astrom: Adaptive Control Around 1960, Proceedings of the 34th Conference on Decision &Control New Orleans, LA (1995).

DOI: 10.1109/cdc.1995.478538

Google Scholar

[3] Jean-Jacques E. Slotine and Weiping Li: Applied Linear Control, Englewood Cliffs, NJ: Prentice Hall (1991).

Google Scholar

[4] Zdenko Kovacic and Stjepan Bogdan: Fuzzy controller design theory and applications, Control engineering series, CRC press (2006).

Google Scholar

[5] G. Saravanakumar, R.S. D Wahidabanu, C.G. Nayak and Thirunavukkarasu : Design and analysis of modified smith predictors for self-regulating and non-self-regulating processes with dead time, Indian Institute of Chemical Engineers Vol. 50 (2008).

DOI: 10.1088/1748-0221/2/08/p08008

Google Scholar

[6] Ibrahim Kaya: A new Smith predictor and controller for control of processes with long dead time, ISA transactions 42 (2003) pp.101-110.

DOI: 10.1016/s0019-0578(07)60117-7

Google Scholar

[7] R. Karthikeyan, Rahul Kumar Yadav, Shikha Tripathi and Hemanth Kumar. G: Analyzing Large Dynamic Set-point change Tracking of MRAC by exploiting Fuzzy Logic based Automatic Gain Tuning, IEEE Control and System Graduate Research Colloquium (ICSGRC 2012).

DOI: 10.1109/icsgrc.2012.6287139

Google Scholar