A frequency domain iterative learning control for low bandwidth system

2001 ◽  
Author(s):  
Wubi Qin ◽  
Lilong Cai
Keyword(s):  
Frequency Domain ◽  
Iterative Learning Control ◽  
Learning Control ◽  
Iterative Learning

scholarly journals Unbalance Compensation of a Full Scale Test Rig Designed for HTR-10GT: A Frequency-Domain Approach Based on Iterative Learning Control

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Ying He ◽  
Lei Shi ◽  
Zhengang Shi ◽  
Zhe Sun
Keyword(s):  
Frequency Domain ◽  
Iterative Learning Control ◽  
Learning Control ◽  
Magnetic Bearing ◽  
Iterative Learning ◽  
Full Scale ◽  
Full Scale Test ◽  
Test Rig ◽  
Operation Speed ◽  
Scale Test

Unbalance vibrations are crucial problems in heavy rotational machinery, especially for the systems with high operation speed, like turbine machinery. For the program of 10 MW High Temperature gas-cooled Reactor with direct Gas-Turbine cycle (HTR-10GT), the rated operation speed of the turbine system is 15000 RPM which is beyond the second bending frequency. In that case, even a small residual mass will lead to large unbalance vibrations. Thus, it is of great significance to study balancing methods for the system. As the turbine rotor is designed to be suspended by active magnetic bearings (AMBs), unbalance compensation could be achieved by adequate control strategies. In the paper, unbalance compensation for the Multi-Input and Multi-Output (MIMO) active magnetic bearing (AMB) system using frequency-domain iterative learning control (ILC) is analyzed. Based on the analysis, an ILC controller for unbalance compensation of the full scale test rig, which is designed for the rotor and AMBs in HTR-10GT, is designed. Simulation results are reported which show the efficiency of the ILC controller for attenuating the unbalance vibration of the full scale test rig. This research can offer valuable design criterion for unbalance compensation of the turbine machinery in HTR-10GT.

Sign in / Sign up

Export Citation Format

Share Document