Reference-free iterative MPC replaces mixed-integer terminal constraints with a learned neural CLBF terminal set and cost, giving conditional recursive feasibility, stability, and non-increasing cost over iterations.
Convergence of constrained model-based predictive control for batch processes,
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Reference-Free Iterative Learning Model Predictive Control with Neural Certificates
Reference-free iterative MPC replaces mixed-integer terminal constraints with a learned neural CLBF terminal set and cost, giving conditional recursive feasibility, stability, and non-increasing cost over iterations.