
Adaptive robust constrained state control for non‐linear maglev vehicle with guaranteed bounded airgap
Author(s) -
Xu Jinquan,
Du Yutao,
Chen YeHwa,
Guo Hong
Publication year - 2018
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2017.1348
Subject(s) - maglev , control theory (sociology) , bounded function , adaptive control , robust control , range (aeronautics) , levitation , chassis , uniform boundedness , engineering , computer science , control engineering , control system , mathematics , control (management) , magnet , mathematical analysis , artificial intelligence , electrical engineering , mechanical engineering , structural engineering , aerospace engineering
The authors propose an adaptive robust control approach for the levitation control of non‐linear maglev vehicle with state constraint. The system contains non‐linear and (possibly) time‐varying uncertainty, which is supposed to be bounded. In order to prevent the undesirable collision, the airgap between suspended chassis and guideway should be restrained in a specified range for safety concerns. Furthermore, the maglev vehicle does not satisfy the (global) matching condition. The authors propose a three‐step state transformation approach to transform the maglev vehicle to an interconnected uncertain system. After that, the robust control is proposed based on the transformed system, and the adaptive law is constructed to emulate the total system uncertainty. The adaptive robust control is able to ensure the system performance (uniform boundedness and the uniform ultimate boundedness) of uncertain maglev vehicle. In addition, the airgap can be confined within the specified range.