Abstract
Fast and accurate positioning and swing minimization of the containers and other loads in crane manipulation are demanding and in the same time conflicting 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.
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