Please use this identifier to cite or link to this item:
Title: Advanced control of active magnetic bearings with learning control schemes
Keywords: Active magnetic bearings, AMB, unbalance compensation, time-domain iterative learning control, automatic learning control, spindle motor
Issue Date: 23-Jan-2005
Citation: WU DEZHENG (2005-01-23). Advanced control of active magnetic bearings with learning control schemes. ScholarBank@NUS Repository.
Abstract: This thesis deals with the unbalance compensation of active magnetic bearings. Time-domain iterative learning control (ILC) scheme and automatic learning control (ALC) scheme are proposed to compensate the unbalance force. ALC is based on time-domain ILC and gain-scheduled control. The controller can obtain the optimized control current for unbalance compensation by iterative learning. In addition, variable learning cycle and variable learning gains are employed in the learning law for better performance against rotational speed fluctuation and ability to work at different speeds. The effectiveness of proposed time-domain ILC and ALC schemes is tested through simulations and experiments. Their performances are compared and the results show that both ILC and ALC have excellent performance during constant speed test. In addition, ALC presents better performance during speed fluctuation and it is effect over a wide range of operation speeds.
Appears in Collections:Master's Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
WuDZ.pdf1.46 MBAdobe PDF



Page view(s)

checked on Feb 10, 2019


checked on Feb 10, 2019

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.