TY - GEN
T1 - Enhanced fuzzy sliding mode control to motion controller of linear induction motor drives
AU - Hsu, Kou Cheng
AU - Chiang, Hsin Han
AU - Huang, Guan Hua
AU - Lee, Tsu Tian
PY - 2014
Y1 - 2014
N2 - In this paper, an enhanced fuzzy sliding mode control system (EFSMC) is proposed for a linear induction motor (LIM) to achieve the position tracking. First, the dynamic model of LIM is investigated for considering the end effect and the friction force into the observer-based compensation design to cope with the time-varying uncertainties. Then, a sliding mode control (SMC) based on the backstepping control technique is presented with the combination of two fuzzy logic controllers. The first fuzzy logic controller is proposed, through a dynamic tune of the sliding surface slope constant of the SMC according to the controlled system states by a fuzzy logic unit. To relax the need of the upper bound of the lumped uncertainties in the SMC, the second fuzzy logic controller is presented, in which the upper bound of the lumped uncertainties can be estimated by a fuzzy inference mechanism. Finally, the experiments for several scenarios are conducted to demonstrate the effectiveness and robustness of the designed controller.
AB - In this paper, an enhanced fuzzy sliding mode control system (EFSMC) is proposed for a linear induction motor (LIM) to achieve the position tracking. First, the dynamic model of LIM is investigated for considering the end effect and the friction force into the observer-based compensation design to cope with the time-varying uncertainties. Then, a sliding mode control (SMC) based on the backstepping control technique is presented with the combination of two fuzzy logic controllers. The first fuzzy logic controller is proposed, through a dynamic tune of the sliding surface slope constant of the SMC according to the controlled system states by a fuzzy logic unit. To relax the need of the upper bound of the lumped uncertainties in the SMC, the second fuzzy logic controller is presented, in which the upper bound of the lumped uncertainties can be estimated by a fuzzy inference mechanism. Finally, the experiments for several scenarios are conducted to demonstrate the effectiveness and robustness of the designed controller.
KW - Sliding mode control
KW - end effect
KW - fuzzy control
KW - linduction motror drives
KW - observer
UR - http://www.scopus.com/inward/record.url?scp=84907069557&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84907069557&partnerID=8YFLogxK
U2 - 10.1109/ICSSE.2014.6887947
DO - 10.1109/ICSSE.2014.6887947
M3 - Conference contribution
AN - SCOPUS:84907069557
SN - 9781479943678
T3 - Conference Proceedings - 2014 International Conference on System Science and Engineering, ICSSE 2014
SP - 268
EP - 272
BT - Conference Proceedings - 2014 International Conference on System Science and Engineering, ICSSE 2014
PB - IEEE Computer Society
T2 - 2014 International Conference on System Science and Engineering, ICSSE 2014
Y2 - 11 July 2014 through 13 July 2014
ER -