2 citations · 2 across the 7 of their papers we have counts for
3 papers · 1 filter
Learning stabilising policies for constrained nonlinear systems
Daniele Ravasio, Danilo Saccani, Marcello Farina +1
This work proposes a two-layered control scheme for constrained nonlinear systems represented by a class of recurrent neural networks and affected by additive disturbances. In part…
Constrained Performance Boosting Control for Nonlinear Systems
Gianluca Giacomelli, Danilo Saccani, Siep Weiland +2
We present the Alternating Direction Method of Multipliers (ADMM) for Performance Boosting (PB), an approach for designing neural controllers for stable nonlinear systems subject t…
MAD: A Magnitude And Direction Policy Parametrization for Stability Constrained Reinforcement Learning
Luca Furieri, Sucheth Shenoy, Danilo Saccani +2
We introduce magnitude and direction (MAD) policies, a policy parameterization for reinforcement learning (RL) that preserves Lp closed-loop stability for nonlinear dynamical syste…