Abstract
A robust control approach for permanent magnet linear synchronous motor servo drive is presented in this work. First, the nonlinear motor dynamics is described in the stationary reference frame instead of the d–q axis synchronous rotating reference frame. Then, a backstepping control technique is employed to the systematic analysis and design of the drive system. To ensure satisfactory performance of the position control, an adaptive fuzzy neural network is introduced to deal with the uncertain dynamics. The online adaptation law is deduced by using the Lyapunov functional method so that the asymptotic stability of the closed-loop system is guaranteed. In contrast to the conventional current vector control strategy, this work develops a voltage control scheme via a complete theoretic derivation, which considers both the mechanical and electrical dynamics of motor’s behavior. Moreover, the proposed control algorithm performs without using the Park and inverse Park coordinate transformations, and the computation efficiency can be improved as a result. Finally, the practical experiment and a comparison study with the conventional current control approach are carried out to illustrate the effectiveness of the proposed control scheme.
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Ting, CS., Lieu, JF., Liu, CS. et al. An Adaptive FNN Control Design of PMLSM in Stationary Reference Frame. J Control Autom Electr Syst 27, 391–405 (2016). https://doi.org/10.1007/s40313-016-0243-5
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DOI: https://doi.org/10.1007/s40313-016-0243-5