Robust adaptive sliding-mode fuzzy-neural-network model-following position control of PMSM servo drives for robotic applications

In this paper, an intelligent sliding-mode controller (SMC) for achieving favorable decoupling control and high precision position tracking performance of permanent-magnet synchronous motor (PMSM) servo drives is proposed. The intelligent position controller consists of a SMC in the position feed-back loop in addition to an online trained fuzzy-neural-network model-following controller (FNNMFC) in the feed-forward loop. The intelligent position controller combines the merits of the SMC with robust characteristics and the FNNMFC with online learning ability for periodic command tracking of a PMSM servo drive. The theoretical analyses of the SMC are described with a second order switching surface which is insensitive to parameters uncertainties and external load disturbances. The FNNMFC generates an adaptive control signal which is added to the SMC output to attain robust model-following characteristics under different operating conditions regardless of parameter uncertainties and load disturbances. The results of simulations confirm that the proposed SMC with FNNMFC grants robust performance and precise response to the reference model regardless of load disturbances and PMSM parameter uncertainties.