Infinite-Horizon Differentiable Model Predictive Control

ICLR 2020 Sebastian EastMarco GallieriJonathan MasciJan KoutnikMark Cannon

This paper proposes a differentiable linear quadratic Model Predictive Control (MPC) framework for safe imitation learning. The infinite-horizon cost is enforced using a terminal cost function obtained from the discrete-time algebraic Riccati equation (DARE), so that the learned controller can be proven to be stabilizing in closed-loop... (read more)

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