Robust model predictive control for non-linear systems with input and state constraints via feedback linearization

摘要: Robust predictive control of non-linear systems under state estimation errors and input constraints is a challenging problem, solutions to it have generally involved solving computationally hard optimizations. Feedback linearization has reduced the computational burden, but not yet been solved for robust model constraints. In this paper, we solve problem system bounded using feedback linearization. We do so by developing on linearized such that respects its These are computed at run-time online reachability, linear in optimization variables, resulting Quadratic Program with also provide feasibility, recursive feasibility stability results our algorithm. evaluate approach two show applicability performance.