Tustin neural networks: a class of recurrent nets for adaptive MPC of mechanical systems

no code implementations • 4 Nov 2019 • Simone Pozzoli, Marco Gallieri, Riccardo Scattolini

The use of recurrent neural networks to represent the dynamics of unstable systems is difficult due to the need to properly initialize their internal states, which in most of the cases do not have any physical meaning, consequent to the non-smoothness of the optimization problem.

Model-based Reinforcement Learning