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Flexible piecewise function evaluation methods with application to explicit model predictive control

机译:灵活的分段函数评估方法及其在显式模型预测控制中的应用

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This paper addresses efficient evaluation of piecewise functions defined over polyhedral partitions which is a vital problem in many areas such as control applications. As an important application, the explicit model predictive control (eMPC) problem is considered which requires a piecewise affine (PWA) control law to be evaluated online. The proposed method combines an Orthogonal Truncated Binary Search Tree (OTBST) and lattice representation for PWA functions in a unified structure enjoying the advantages of both approaches. The proposed Lattice-based OTBST (LOTBST) method enables the designer to trade-off between preprocessing time, storage requirement and online computation time. Using examples it is shown that the proposed LOTBST leads to a considerably less preprocessing time and memory requirement comparing to the pure BST and less online computation time comparing to the pure lattice representation.
机译:本文解决了在多面体分区上定义的分段函数的有效评估,这在许多领域(例如控制应用)中都是至关重要的问题。作为一项重要应用,考虑了显式模型预测控制(eMPC)问题,该问题要求分段仿射(PWA)控制定律可以在线评估。所提出的方法在统一的结构中结合了正交截断二叉搜索树(OTBST)和PWA函数的晶格表示,同时兼顾了这两种方法的优点。所提出的基于格子的OTBST(LOTBST)方法使设计人员能够在预处理时间,存储需求和在线计算时间之间进行权衡。通过示例可以看出,与纯BST相比,所建议的LOTBST导致的预处理时间和内存需求明显减少,与纯晶格表示相比,该算法导致的在线计算时间更少。

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