Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/192
Title: Kalman State Estimation and LQR Assisted Adaptive Control Of a Variable Loaded Servo System
Authors: Aydoğdu, Ömer
Levent, Mehmet Latif
Keywords: adaptive control
Lyapunov method
LQR
Kalman filter
VLS system
Issue Date: 2019
Publisher: EOS ASSOC
Abstract: This study actualized a new hybrid adaptive controller design to increase the control performance of a variable loaded time-varying system. A structure in which LQR and adaptive control work together is proposed. At first, a Kalman filter was designed to estimate the states of the system and used with the LQR control method which is one of the optimal control servo system techniques in constant initial load. Then, for the variable loaded servo (VLS) system, the Lyapunov based adaptive control was added to the LQR control method which was inadequate due to the constant gain parameters. Thus, it was aimed to eliminate the variable load effects and increase the stability of the system. In order to show the effectiveness of the proposed method, a Quanser servo module was used in Matlab-Simulink environment. It is seen from the experimental results and performance measurements that the proposed method increases the system performance and stability by minimizing noise, variable load effect and steady-state error.
URI: https://hdl.handle.net/20.500.13091/192
ISSN: 2241-4487
1792-8036
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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