Abstract
Extreme learning adaptive neuro-fuzzy inference system (ELANFIS) helps in combining the understanding capabilities of extreme learning machine (ELM) and the clear knowledge of the TSK fuzzy systems. This paper proposes tip position control of flexible link manipulator along with tip vibration suppression using ELANFIS. Using assumed model method and Lagrangian mechanics, a nonlinear dynamic model of flexible link manipulator is derived. A control strategy based on ELANFIS inverse model has been designed for precise position tracking. Numerical simulations are adopted for checking the effectiveness and viability of the proposed control algorithm. The performances of the proposed controller has been compared with LQR and neural network controllers.
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