Abstract
A self‐constructing Sugeno type adaptive fuzzy neural network (SAFNN) control system is proposed in this study for the contour tracking control of a two‐axis motion control system. The adopted two‐axis motion control system is composed of two permanent magnet linear synchronous motors (PMLSMs). The proposed SAFNN combines the merits of a self‐constructing fuzzy neural network (SCFNN) and a TSK‐type fuzzy inference mechanism. Moreover, the structure and the parameter learning phases are performed concurrently and on line in the SAFNN. The structure learning is based on the partition of input space, and the parameter learning is based on the supervised gradient descent method using a delta adaptation law. Furthermore, the proposed control algorithms are implemented in a TMS320C32 DSP‐based control computer. From the simulated and experimental results, the contour tracking performance of the two‐axis motion control system is significantly improved and robustness can be obtained as well using the proposed SAFNN control system.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
