Tensor product based control of the Single Pendulum Gantry process with stable neural network based friction compensation

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 effect, especially in the low speed region. In this paper authors propose position controller realized as hybrid controller. It consists of the tensor product based nonlinear feedback controller with additional friction self-learning neural compensator. The experimental results show that friction compensator is able to remove position error in steady state.