Time-Delay Identification and Validation of a Liquid Film Transport Model based on Pilot Plant Experiments

Hofmann, Julian; Ponomarev, Anton; Hagenmeyer, Veit; Gröll, Lutz

doi:10.1016/j.ifacol.2021.08.275

Cited by 2 publications

(2 citation statements)

References 7 publications

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“…3 . As no direct measurement of ˙ m o, T is available, we calculate it via numerical differentiation of the water level in the reservoir after the tube and, to this end, basic moving average filter is used ( Hofmann et al, 2021 ). In this experiment, we observe both the delayed response and the overshoot.…”

Section: Ffe Pass Modelmentioning

confidence: 99%

Novel Control-Oriented Models for Liquid Transport in Falling Film Evaporator Tubes

Ponomarev

Hofmann

Gröll

2021

Computers & Chemical Engineering

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Section: Ffe Pass Modelmentioning

confidence: 99%

Novel Control-Oriented Models for Liquid Transport in Falling Film Evaporator Tubes

Ponomarev

Hofmann

Gröll

2021

Computers & Chemical Engineering

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“…Wang et al [ 15 ] proposed a parameter identification method of a fractional-order time delay system based on the Legendre wavelet, which reduces the effect of noise on the accuracy of parameter identification. Hofmann et al [ 16 ] proposed an offline time-delay identification strategy based on falling film evaporator pilot plant experiments and obtained good results in both validation experiments, with and without evaporation. Prasad et al [ 17 ] used fractional-order modeling technique to identify the parameters of Hammerstein structured nonlinear systems with discontinuous asymmetric (two segment piecewise-linear with a dead-zone) nonlinearity and input time delay.…”

Section: Introductionmentioning

confidence: 99%

Multi-Delay Identification of Rare Earth Extraction Process Based on Improved Time-Correlation Analysis

Liu

Yang

et al. 2023

Sensors

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The rare earth extraction process has significant time delay characteristics, making it challenging to identify the time delay and establish an accurate mathematical model. This paper proposes a multi-delay identification method based on improved time-correlation analysis. Firstly, the data are preprocessed by grey relational analysis, and the time delay sequence and time-correlation data matrix are constructed. The time-correlation analysis matrix is defined, and the H∞ norm quantifies the correlation degree of the data sequence. Thus the multi-delay identification problem is transformed into an integer optimization problem. Secondly, an improved discrete state transition algorithm is used for optimization to obtain multi-delay. Finally, based on an Neodymium (Nd) component content model constructed by a wavelet neural network, the performance of the proposed method is compared with the unimproved time delay identification method and the model without an identification method. The results show that the proposed algorithm improves optimization accuracy, convergence speed, and stability. The performance of the component content model after time delay identification is significantly improved using the proposed method, which verifies its effectiveness in the time delay identification of the rare earth extraction process.

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Time-Delay Identification and Validation of a Liquid Film Transport Model based on Pilot Plant Experiments

Cited by 2 publications

References 7 publications

Novel Control-Oriented Models for Liquid Transport in Falling Film Evaporator Tubes

Novel Control-Oriented Models for Liquid Transport in Falling Film Evaporator Tubes

Multi-Delay Identification of Rare Earth Extraction Process Based on Improved Time-Correlation Analysis

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