A learned policy rollout is refined by one Newton step via Riccati recursion, yielding quadratic reduction in suboptimality for nonlinear MPC, shown on quadcopter trajectory tracking.
Stability analysis of nonlinear model predictive control with progressive tightening of stage costs and constraints,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.OC 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Rollout Then Optimize: A One-Step Newton Refinement of Learned Policies for Nonlinear Model Predictive Control
A learned policy rollout is refined by one Newton step via Riccati recursion, yielding quadratic reduction in suboptimality for nonlinear MPC, shown on quadcopter trajectory tracking.