TY - JOUR
T1 - FPGA-based intelligent-complementary sliding-mode control for PMLSM servo-drive system
AU - Lin, Faa Jeng
AU - Hwang, Jonq Chin
AU - Chou, Po Huan
AU - Hung, Ying Chih
N1 - Funding Information:
Manuscript received June 11, 2009; revised July 23, 2009, September 21, 2009, December 14, 2009, and March 7, 2010; accepted May 11, 2010. Date of current version September 17, 2010. This work was supported by the National Science Council of Taiwan, under Grant NSC 95-2221-E-008-177-MY3. Recommended for publication by Associate Editor K.-B. Lee. F.-J. Lin and Y.-C. Hung are with the Department of Electrical Engineering, National Central University, Chungli 320, Taiwan. J.-C. Hwang is with the Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 106, Taiwan. P.-H. Chou is with the Department of Electrical Engineering, National Dong Hwa University, Hualien 974, Taiwan (e-mail: [email protected]). Digital Object Identifier 10.1109/TPEL.2010.2050907
PY - 2010
Y1 - 2010
N2 - A field-programmable gate array (FPGA)-based intelligent-complementary sliding-mode control (ICSMC) is proposed in this paper to control the mover of a permanent magnet linear synchronous motor (PMLSM) servo-drive system to track periodic-reference trajectories. First, the dynamics of the field-oriented control PMLSM servo drive with a lumped uncertainty, which contains parameter variations, external disturbances, and nonlinear-friction force, is derived. Then, to achieve the required high-control performance, the ICSMC is developed. In this approach, a radial-basis function-network (RBFN) estimator with accurate approximation capability is employed to estimate the lumped uncertainty directly. Moreover, the adaptive-learning algorithms for the online training of the RBFN are derived using the Lyapunov theorem to guarantee the closed-loop stability. Furthermore, the FPGA chip is adopted to implement the developed control and online learning algorithms for possible low-cost and high-performance industrial applications using PMLSM. Finally, some experimental results are illustrated to show the validity of the proposed control approach.
AB - A field-programmable gate array (FPGA)-based intelligent-complementary sliding-mode control (ICSMC) is proposed in this paper to control the mover of a permanent magnet linear synchronous motor (PMLSM) servo-drive system to track periodic-reference trajectories. First, the dynamics of the field-oriented control PMLSM servo drive with a lumped uncertainty, which contains parameter variations, external disturbances, and nonlinear-friction force, is derived. Then, to achieve the required high-control performance, the ICSMC is developed. In this approach, a radial-basis function-network (RBFN) estimator with accurate approximation capability is employed to estimate the lumped uncertainty directly. Moreover, the adaptive-learning algorithms for the online training of the RBFN are derived using the Lyapunov theorem to guarantee the closed-loop stability. Furthermore, the FPGA chip is adopted to implement the developed control and online learning algorithms for possible low-cost and high-performance industrial applications using PMLSM. Finally, some experimental results are illustrated to show the validity of the proposed control approach.
KW - Complementary sliding-mode control
KW - fieldprogrammable gate array (FPGA)
KW - permanent-magnet linearsynchronous motor (PMLSM)
KW - radial-basis function network (RBFN)
UR - http://www.scopus.com/inward/record.url?scp=77957731745&partnerID=8YFLogxK
U2 - 10.1109/TPEL.2010.2050907
DO - 10.1109/TPEL.2010.2050907
M3 - 期刊論文
AN - SCOPUS:77957731745
SN - 0885-8993
VL - 25
SP - 2573
EP - 2587
JO - IEEE Transactions on Power Electronics
JF - IEEE Transactions on Power Electronics
IS - 10
M1 - 5467185
ER -