7 citations · 10 across the 10 of their papers we have counts for
3 papers · 1 filter
Feedforward Controllers from Learned Dynamic Local Model Networks with Application to Excavator Assistance Functions
Leon Greiser, Ozan Demir, Benjamin Hartmann +2
Complicated first principles modelling and controller synthesis can be prohibitively slow and expensive for high-mix, low-volume products such as hydraulic excavators. Instead, in…
Parameter-Adaptive Approximate MPC: Tuning Neural-Network Controllers without Retraining
Henrik Hose, Alexander Gräfe, Sebastian Trimpe
Model Predictive Control (MPC) is a method to control nonlinear systems with guaranteed stability and constraint satisfaction but suffers from high computation times. Approximate M…
Approximate non-linear model predictive control with safety-augmented neural networks
Henrik Hose, Johannes Köhler, Melanie N. Zeilinger +1
Model predictive control (MPC) achieves stability and constraint satisfaction for general nonlinear systems, but requires computationally expensive online optimization. This paper…