A set-membership data-driven min-max MPC approach is developed for unknown nonlinear systems, yielding recursive feasibility and stability guarantees via Lyapunov SDPs for noise-free and disturbed measurements.
arXiv:2401.04660 , month =
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Data-Driven Robust MPC for Unknown Nonlinear Systems via Set-Membership Learning
A set-membership data-driven min-max MPC approach is developed for unknown nonlinear systems, yielding recursive feasibility and stability guarantees via Lyapunov SDPs for noise-free and disturbed measurements.