DocumentCode :
1706417
Title :
Kautz-based adaptive control
Author :
Taheri, Ehsan
Author_Institution :
Tehran, Iran
fYear :
2008
Firstpage :
619
Lastpage :
623
Abstract :
The main purpose of this paper has been to investigate algorithms for adaptive control base on unstructured identification. Control low is a hybrid of two algorithms. Model reference and transfer function shaping are mixed and finally a new approach with all advantage of these two algorithms is obtained. Fundamental problems associated in adaptive control are: 1. The requirement of an exact prior system information such as degree and delay. 2. Sensitivity to variations of the system time delay. For solving these problems unstructured identification is offered. One of the most famous of OFS model is Kautz network that used. Particular systems can be well approximated by using Kautz model with complex poles. This method covers a wide range of stable linear systems, namely minimum phase, non-minimum phase and time delay systems.
Keywords :
adaptive control; delay systems; identification; nonlinear control systems; transfer functions; Kautz-based adaptive control; linear systems; nonminimum phase systems; time delay systems; transfer function shaping; unstructured identification; Adaptive control; Additive noise; Control systems; Delay effects; Nonlinear control systems; Optimal control; Programmable control; System identification; Transfer functions; Uncertainty; Adaptive control; Kautz network; Unstructured identification; Unstructured uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications, Control and Signal Processing, 2008. ISCCSP 2008. 3rd International Symposium on
Conference_Location :
St Julians
Print_ISBN :
978-1-4244-1687-5
Electronic_ISBN :
978-1-4244-1688-2
Type :
conf
DOI :
10.1109/ISCCSP.2008.4537299
Filename :
4537299
Link To Document :
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