Fehr, JörgSchmid, PatrickSchneider, GeorgEberhard, Peter2020-10-302020-10-3020202076-34171737490315http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-111185http://elib.uni-stuttgart.de/handle/11682/11118http://dx.doi.org/10.18419/opus-11101A model predictive control (MPC) scheme for a Schunk PowerCube robot is derived in a structured step-by-step procedure. Neweul-M² provides the necessary nonlinear model in symbolical and numerical form. To handle the heavy online computational burden concerning the derived nonlinear model, a linear time-varying MPC scheme is developed based on linearizing the nonlinear system concerning the desired trajectory and the a priori known corresponding feed-forward controller. Camera-based systems allow sensing of the robot on the one hand and monitoring the environments on the other hand. Therefore, a vision-based MPC is realized to show the effects of vision-based control feedback on control performance. A semi-automatic trajectory planning is used to perform two meaningful experimental studies in which the advantages and restrictions of the proposed (vision-based) linear time-varying MPC scheme are pointed out. Everything is implemented on a slim, low-cost control system with a standard laptop PC.eninfo:eu-repo/semantics/openAccess620article