Autors: Dimitrov N. D., Ahmed, S. A., Topalov, A. V., Radev P.
Title: Implementing Neuro-Adaptive Control Algorithms with Sliding Mode Learning on Industrial Servo Drives
Keywords: sliding mode learning, stability, adaptive control, servo sy

Abstract: The demand of the industry for high performance electric motors has significantly increased nowadays. This has boosted the usage of permanent magnet brushless synchronous motors (BLSM) in many applications where the accuracy and performance requirements are high. Further improvement of the BLSM drive systems performance can be achieved by providing them with adaptive control capabilities. The relative complexity of adaptive control schemes and algorithms and the computational load that they impose have prevented until recently their practical implementation into the industrial servo systems. In this investigation, a neuro-adaptive control scheme where the rule for parameter adaptation is designed by taking into account the variable structure control (VSC) concepts and Lyapunov stability, is proposed and embedded into an inexpensive, available on the market, position control system for brushless synchronous servomotors.



    4th International Conference on Systems and Informatics (ICSAI), pp. 110-115, 2017, China, IEEE, DOI 10.1109/ICSAI.2017.8248273

    Copyright IEEE

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus и Web of Science