Dynamics and Iterative Learning Control of Robots with Parallel Kinematical Structures

The paper deals with model-based control of robots with parallel kinematical structure (PKM). At first, an approach for the identification of friction and rigid-body dynamics of complex parallel kinematical structures is presented. The approach is based on optimal excitation trajectories. The trajectories are bounded, such they are easy to be fit into the small and hard constraint workspace of PKM. Secondly, some results are presented using feedforward control in order to compensate nonlinear dynamical influences. Thirdly, Iterative Learning Control (ILC) is proposed in this paper for tracking accuracy enhancement of a parallel direct driven manipulator. It is shown both by means of simulation study and experimental results that linear ILC is appropriate for application to the considered high nonlinear and coupled systems.