用改进的分段线性Hammerstein模型识别控制回路中的阀门粘滞

Jiravit Pratvittaya, S. Wongsa
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引用次数: 1

摘要

这项工作的动机是通过分段线性Hammerstein (PWL-HMM)识别对粘性控制阀进行建模。在PWL-HMM中,阀门的非线性部分,即粘性,由基于点斜率的迟滞模型描述,其中必须为阀门位置信号的上升和下降路径定义一组结点。传统上假设结点是均匀分布的,这可能会导致模型中包含一些不相关的结点。我们提出了两种方法来解决这个问题,即基于恒定阈值和基于bic的结减少,以识别这些不相关的结,并改进PWL的粘滞模型。通过数值、实验和工业算例验证了所提出的结精化方法的有效性。
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Identification of Valve Stiction in Control Loops Using Refined Piecewise-Linear Hammerstein Models
This work is motivated by the modelling of sticky control valves via the piecewise linear Hammerstein (PWL-HMM) identification. In PWL-HMM, the nonlinear part of the valve, i.e. stiction, is described by a point-slope-based hysteresis model where a set of knots have to be defined for both the ascent and descent paths of the valve position signal. Traditionally, the knots are assumed to be uniformly distributed, as a result some irrelevant knots might be included in the model. We tackle this problem by proposing two methods, namely the constant threshold-based and BIC-based knot reductions, to identify such irrelevant knots and refine the PWL model of stiction. Numerical, experimental and industrial examples are provided to illustrate the effectiveness of the proposed knot refinement methods.
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