arXiv:2212.12414

Set Membership based Nonlinear Model Predictive Control

Mattia Boggio, Carlo Novara, Michele Taragna

제출 2022-12-23

원문 초록

We present a numerically efficient Nonlinear Model Predictive Control (NMPC) approach, called Set Membership based NMPC (SM-NMPC). In particular, a Set Membership method is used to derive from data an approximation and tight bounds on the optimal NMPC control law. These quantities are used to reduce the dimensionality and volume of the search domain of the NMPC optimization problem, allowing a significant shortening of the computation time. The proposed SM-NMPC strategy is tested in simulation, considering realistic autonomous vehicle scenarios, like parallel parking and lane keeping maneuvers.

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arXiv:2505.01059공통 태그 model, Model Predictive Control공식 코드 · Papers with Code

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