TY - JOUR
T1 - Sliding mode control of SPMSM drivers
T2 - An online gain tuning approach with unknown system parameters
AU - Jung, Jin Woo
AU - Leu, Viet Quoc
AU - Dang, Dong Quang
AU - Choi, Han Ho
AU - Kim, Tae Heoung
N1 - Publisher Copyright:
© 2014 KIPE.
PY - 2014
Y1 - 2014
N2 - This paper proposes an online gain tuning algorithm for a robust sliding mode speed controller of surface-mounted permanent magnet synchronous motor (SPMSM) drives. The proposed controller is constructed by a fuzzy neural network control (FNNC) term and a sliding mode control (SMC) term. Based on a fuzzy neural network, the first term is designed to approximate the nonlinear factors while the second term is used to stabilize the system dynamics by employing an online tuning rule. Therefore, unlike conventional speed controllers, the proposed control scheme does not require any knowledge of the system parameters. As a result, it is very robust to system parameter variations. The stability evaluation of the proposed control system is fully described based on the Lyapunov theory and related lemmas. For comparison purposes, a conventional sliding mode control (SMC) scheme is also tested under the same conditions as the proposed control method. It can be seen from the experimental results that the proposed SMC scheme exhibits better control performance (i.e., faster and more robust dynamic behavior, and a smaller steady-state error) than the conventional SMC method.
AB - This paper proposes an online gain tuning algorithm for a robust sliding mode speed controller of surface-mounted permanent magnet synchronous motor (SPMSM) drives. The proposed controller is constructed by a fuzzy neural network control (FNNC) term and a sliding mode control (SMC) term. Based on a fuzzy neural network, the first term is designed to approximate the nonlinear factors while the second term is used to stabilize the system dynamics by employing an online tuning rule. Therefore, unlike conventional speed controllers, the proposed control scheme does not require any knowledge of the system parameters. As a result, it is very robust to system parameter variations. The stability evaluation of the proposed control system is fully described based on the Lyapunov theory and related lemmas. For comparison purposes, a conventional sliding mode control (SMC) scheme is also tested under the same conditions as the proposed control method. It can be seen from the experimental results that the proposed SMC scheme exhibits better control performance (i.e., faster and more robust dynamic behavior, and a smaller steady-state error) than the conventional SMC method.
KW - Fuzzy neural network control (FNNC)
KW - Sliding mode control (SMC)
KW - Speed control
KW - Surface-mounted permanent magnet synchronous motor (SPMSM)
KW - System parameter variations
UR - http://www.scopus.com/inward/record.url?scp=85006515951&partnerID=8YFLogxK
U2 - 10.6113/JPE.2014.14.5.980
DO - 10.6113/JPE.2014.14.5.980
M3 - Article
AN - SCOPUS:85006515951
SN - 1598-2092
VL - 14
SP - 980
EP - 988
JO - Journal of Power Electronics
JF - Journal of Power Electronics
IS - 5
M1 - JPE 14-5-19
ER -