A backstepping-derived reach-avoid invariant set serves as the terminal constraint in sampled-data MPC, proving recursive feasibility and safe steering to the target for continuous nonlinear systems under input constraints and fast sampling.
Backstepping reach-avoid con- troller synthesis for multi-input multi-output systems with mixed relative degrees
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Reach-Avoid Model Predictive Control with Guaranteed Recursive Feasibility via Input Constrained Backstepping
A backstepping-derived reach-avoid invariant set serves as the terminal constraint in sampled-data MPC, proving recursive feasibility and safe steering to the target for continuous nonlinear systems under input constraints and fast sampling.