Combining multi-level real-time iterations of Nonlinear Model Predictive Control to realize squatting motions on Leo

Today’s humanoid robots are complex mechanical systems with many degrees of freedom that are built to achieve locomotion skills comparable to humans. In order to synthesize whole-body motions, real-tme capable direct methods of optimal control are a subject of contemporary research. To this end, Nonlinear Model Predictive Control is the method...

Challenges for process system engineering in infrastructure operation and control

The need for improving the operation and control of infrastructure systems has created a demand on optimization methods applicable in the area of complex sociotechnical systems operated by a multitude of actors in a setting of decentralized decision making. This paper briefly presents main classes of optimization models applied in PSE system...

Multi-agent model predictive control for transportation networks: Serial versus parallel schemes

We consider the control of large-scale transportation networks, like road traffic networks, power distribution networks, water distribution networks, etc. Control of these networks is often not possible from a single point by a single intelligent control agent; instead control has to be performed using multiple intelligent agents. We consider...