AI RESEARCH
Bilinear Mamba-Koopman Neural MPC for Varying Dynamics
arXiv CS.LG
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ArXi:2605.04793v1 Announce Type: new Koopman-based neural MPC models generate time-varying dynamics from historical data, but preserve convexity by enforcing that the system operator is independent of the current control input. This conditional independence constraint limits adaptation to changing dynamics within a single MPC horizon, particularly under time-varying conditions and under stale-plan execution.