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首页> 外文期刊>Optimal Control Applications and Methods >Solving mixed-integer optimal control problems by branch&bound: a case study from automobile test-driving with gear shift
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Solving mixed-integer optimal control problems by branch&bound: a case study from automobile test-driving with gear shift

机译:用分支定界法解决混合整数最优控制问题:以换挡汽车试驾为例

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The article discusses the application of the branch&bound method to a mixed integer non-linear optimization problem (MINLP) arising from a discretization of an optimal control problem with partly discrete control set. The optimal control problem has its origin in automobile test-driving, where the car model involves a discrete-valued control function for the gear shift. Since the number of variables in (MINLP) grows with the number of grid points used for discretization of the optimal control problem, the example from automobile test-driving may serve as a benchmark problem of scalable complexity. Reference solutions are computed numerically for two different problem sizes. A simple heuristic approach suitable for optimal control problems is suggested that reduces the computational amount considerably, though it cannot guarantee optimality anymore.
机译:本文讨论了分支约束方法在混合整数非线性优化问题(MINLP)中的应用,该问题由具有部分离散控制集的最优控制问题离散化而成。最佳控制问题起源于汽车试驾,其中汽车模型涉及用于变速的离散值控制功能。由于(MINLP)中的变量数量随用于离散化最佳控制问题的网格点数量而增长,因此来自汽车测试驾驶的示例可以作为可扩展复杂性的基准问题。对于两个不同的问题大小,将通过数字计算参考解决方案。提出了一种适用于最优控制问题的简单启发式方法,尽管它不能再保证最优性,但可以大大减少计算量。

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