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A moving horizon technique for the simulation of automobile test‐drives
Author(s) -
Gerdts M.
Publication year - 2003
Publication title -
zamm ‐ journal of applied mathematics and mechanics / zeitschrift für angewandte mathematik und mechanik
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.449
H-Index - 51
eISSN - 1521-4001
pISSN - 0044-2267
DOI - 10.1002/zamm.200310015
Subject(s) - discretization , optimal control , nonlinear system , control theory (sociology) , transient (computer programming) , dimension (graph theory) , mathematical optimization , range (aeronautics) , stability (learning theory) , optimization problem , computer science , horizon , mathematics , control (management) , engineering , mathematical analysis , artificial intelligence , physics , quantum mechanics , machine learning , pure mathematics , aerospace engineering , operating system , geometry
The test‐drive of an automobile along a given test‐course can be modeled by formulation of a suitable optimal control problem. For the numerical solution the optimal control problem is discretized by a direct shooting method and transformed into a finite dimensional nonlinear optimization problem. With increasing length of the test‐course, the dimension of the nonlinear optimization problem increases as well and its numerical solution becomes very difficult due to stability reasons. Therefore a moving horizon technique with reduced range of vision for the test‐driver is introduced. Instead of treating the complete test‐course, a comparatively short local sector is considered on which a corresponding local optimal control problem can be solved comfortably. The local solutions are then combined by suitable transient conditions. A numerical example with a realistic car model is given.