Subspace identification based predictive control of Wiener system

Qipei Yang; Qibing Jin; Yang Zhang

doi:10.1117/12.2686470

10 August 2023 Subspace identification based predictive control of Wiener system

Qipei Yang, Qibing Jin, Yang Zhang

Proceedings Volume 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023); 127590V (2023) https://doi.org/10.1117/12.2686470
Event: 2023 3rd International Conference on Automation Control, Algorithm and Intelligent Bionics (ACAIB 2023), 2023, Xiamen, China

Abstract

The predictive control of Wiener systems involving modeling nonlinearities is of great importance for analyzing industrial processes. In this paper, a data-driven predictive control method for Wiener systems is proposed. The methods used in this paper are based on some common simple linear algebra tools such as least squares and QR decomposition, where no complex solution process is involved, resulting in high estimation accuracy and numerical robustness. the data-driven predictive controller is designed according to the subspace predictor. The simulation results reveal that the proposed method are more accuracy and stable in Wiener model predictive control.

Citation Download Citation

Qipei Yang, Qibing Jin, and Yang Zhang "Subspace identification based predictive control of Wiener system", Proc. SPIE 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023), 127590V (10 August 2023); https://doi.org/10.1117/12.2686470

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