Abstract
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.
Funder
the National Key R&D Program of China
the Open Fund of State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University
the National Natural Science Foundation of China
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Reference38 articles.
1. Bilinear model of rare earth cascade extraction process and its parameter identification;Jia;Control Theory Appl.,2006
2. Modeling and simulation of multicomponent solvent extraction processes to purify rare earth metals;Chan;Hydrometallurgy,2016
3. Simulation of rare earth extraction process based on separation coefficient correction;Yang;CIESC J.,2020
4. Robust identification of continuous systems with dead-time from step responses;Wang;Automatica,2001
5. Step response-based identification of fractional order time delay models;Salim;Circuits Syst. Signal Process.,2020
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