比例电磁阀动力学系统辨识。

IF 0.6 Q4 AUTOMATION & CONTROL SYSTEMS International Journal of Modelling Identification and Control Pub Date : 2020-01-01 Epub Date: 2020-10-13 DOI:10.1504/ijmic.2020.10032851
Bakir Hajdarevic, Jacob Herrmann, Andrea Fonseca da Cruz, David W Kaczka
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引用次数: 1

摘要

我们提出了一种系统识别技术,用于表征PSOL阀及其相应的电子控制单元(ECU)的线性和动态响应,该技术使用限带白噪声以及由互素数频率组成的伪随机“非和非差”(NSND)波形,以减轻非线性失真的影响。采用非线性梯度下降法从电压流频率响应中同时估计出多个传递函数模型的参数。使用均方残差(MSR)准则和修正的赤池信息准则(AICc)评估候选传递函数模型。MSR产生了一个由10个极点和9个零组成的传递函数,而AICc产生了一个由5个极点和3个零组成的更简单的传递函数。蒙特卡罗分析表明,msr选择的模型在估计的不确定性范围内相对于不同的参数值具有脆弱的稳定性,而aicc选择的模型具有稳健的稳定性。
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System identification of proportional solenoid valve dynamics.

We present a system identification technique for the characterisation of the linearity and dynamic response of a PSOL valve and its corresponding electronic control unit (ECU) using bandlimited white noise, as well as pseudo random "non-sum non-difference" (NSND) waveforms consisting of mutually prime frequencies to mitigate the effects of nonlinear distortions. The parameters of several transfer function models were simultaneously estimated from the voltage-flow frequency response using a nonlinear gradient descent technique. Candidate transfer function models were assessed using the mean squared residual (MSR) criterion and the corrected Akaike information criterion (AICc). The MSR yielded a transfer function consisting of 10 poles and 9 zeros, while the AICc yielded a simpler transfer function consisting of 5 poles and 3 zeros. Monte Carlo analysis demonstrated fragile stability for the MSR-selected model with respect to varying parameter values within estimated uncertainties, yet a robust stability for the AICc-selected model.

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来源期刊
CiteScore
1.70
自引率
57.10%
发文量
52
期刊介绍: Most of the research and experiments in the fields of science, engineering, and social studies have spent significant efforts to find rules from various complicated phenomena by observations, recorded data, logic derivations, and so on. The rules are normally summarised as concise and quantitative expressions or “models". “Identification" provides mechanisms to establish the models and “control" provides mechanisms to improve the system (represented by its model) performance. IJMIC is set up to reflect the relevant generic studies in this area.
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