engleski

Friction compensation of gantry crane model based on the B-spline neural compensator

Fast and accurate positioning and swing min- imization of the containers and other loads in crane ma- nipulation are demanding and in the same time conflict- ing tasks. For accurate positioning, the main problem is nonlinear friction compensation, especially in the low speed region. In this paper authors propose position controller realized as hybrid controller. It consists of the conventional linear state feedback controller with additional friction self- learning neural compensator in the feedforwad loop. Self- learning compensator is based on the B- spline artificial neural network which consists of the one hidden layer of the B-spline second order functions. The experimental results show that friction compensator is able to remove position error in steady state.

Single Pendulum Gantry; Neural Network; Friction Compensation; B-spline network; on-line network learning.

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