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A Scalable Learned Iterative Solver for Nonlinear MPC via Temporal Decomposition
Nonlinear model predictive control (NMPC) can be applied to large nonlinear systems with complex objectives while enforcing constraints, but the cost of solving the underlying optimization problems limits real-time application for systems with fast dynamics or many states. Neural networks can reduce
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