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The influence of finite word length representation of the delta predictive controller design for automotive powertrain systems

机译:有限字长表示对汽车动力总成系统增量预测控制器设计的影响

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The automotive systems contain fast processes that implies fast sampling rate. Moreover, the existing digital hardware contains processing registers that have finite precision and therefore, the representation can be restricted to a finite number of bits. Predictive control strategy in discrete δ domain, State Space δ Generalised Predictive Control, in particular, referred as SS δ GPC algorithm, can bring significant improvements in terms of choosing a small sampling period combined with finite word length representation. The aim of this paper is to emphasize the advantages of the SS δ GPC algorithm, compared to the classical GPC strategy for different word length representation.
机译:汽车系统包含的快速过程意味着快速的采样率。而且,现有的数字硬件包含具有有限精度的处理寄存器,因此,可以将表示限制为有限数量的位。离散δ域中的预测控制策略,即状态空间δ广义预测控制,特别是被称为SSδGPC算法,可以在选择小采样周期与有限字长表示相结合方面带来显着的改进。本文的目的是强调与传统GPC策略相比,SSδGPC算法在不同字长表示上的优势。

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