Abstract
A three-degree-of-freedom (3-DOF) dynamic model based interval type-2 recurrent fuzzy neural network (IT2RFNN) control system is proposed in this study for a gantry position stage. To consider the effect of inter-axis mechanical coupling, a Lagrangian equation based 3-DOF dynamic model for gantry position stage is derived first. Then, to minimize the synchronous error and tracking error of the gantry position stage, the 3-DOF dynamic model based IT2RFNN control system is proposed. In this approach, the adaptive learning algorithms of the IT2RFNN on-line are derived from the Lyapunov stability theorem. Finally, some experimental results of optical inspection application are illustrated to show the validity of the proposed control approach.
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