DocumentCode :
3402121
Title :
Model-Free Control Design for Hybrid Magnetic Levitation System
Author :
Wai, Rong-Jong ; Lee, Jeng-Dao ; Liao, Chiung-Chou
Author_Institution :
Dept. of Electr. Eng., Yuan Ze Univ., Chung Li
fYear :
2005
fDate :
25-25 May 2005
Firstpage :
933
Lastpage :
938
Abstract :
This study investigates three model-free control strategies including a simple proportional-integral-differential (PID) scheme, a fuzzy-neural-network (FNN) control and a robust control for a hybrid magnetic levitation (maglev) system. In general, the lumped dynamic model of a hybrid maglev system can be derived by the transforming principle from electrical energy to mechanical energy. In practice, this hybrid maglev system is inherently unstable in the direction of levitation, and the relationships among airgap, current and electromagnetic force are highly nonlinear, therefore, the mathematical model can not be established precisely. In order to cope with the unavailable dynamics, model-free control design is always required to handle the system behaviors. In this study, the experimental comparison of PID, FNN and robust control systems for the hybrid maglev system is reported. From the performance comparison, the robust control system yields superior control performance than PID and FNN control systems. Moreover, it not only has the learning ability similar to FNN control, but also the simple control structure to the PID control
Keywords :
control system synthesis; fuzzy control; fuzzy neural nets; learning (artificial intelligence); magnetic levitation; neurocontrollers; railways; robust control; three-term control; FNN control; PID control; airgap; electrical energy; electromagnetic force; fuzzy-neural-network control; hybrid magnetic levitation system; learning; lumped dynamic model; maglev system; mechanical energy; model-free control design; proportional-integral-differential control; robust control; system behavior; Control design; Control systems; Fuzzy control; Magnetic levitation; Mechanical energy; Nonlinear dynamical systems; Pi control; Proportional control; Robust control; Three-term control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 2005. FUZZ '05. The 14th IEEE International Conference on
Conference_Location :
Reno, NV
Print_ISBN :
0-7803-9159-4
Type :
conf
DOI :
10.1109/FUZZY.2005.1452519
Filename :
1452519
Link To Document :
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