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Hung, Pham Van
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Electrical & Electronics Engineering

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Journal : Bulletin of Electrical Engineering and Informatics

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Backstepping control with radial basis function neural network for web transport systems Ly, Tong Thi; Loc, Vu Gia; Thang, Dao Duc; Hung, Pham Van; Huong, Trinh Thi Thu; Duc, Duong Minh
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5392

Abstract

Web transport system (WTS) is commonly used in the production and handling of web materials such as paper, fabric, corrugated iron, steel, and printing operations. These materials are easily damaged if the process performance is poor. Therefore, high technology in mechanics and precise control techniques are required in this system. In addition, because of parameter variation, strong nonlinearity, and many external noises, there are many challenges in controlling this process. This paper proposes a backstepping technique-based algorithm to control the web’s tension and velocity. To solve the parameter variation, a radial basis function (RBF) neural network-based adaptation algorithm is developed to approximate the varied components in the control algorithm. The system stability is guaranteed using the Lyapunov stability theorem. Simulations in MATLAB/Simulink have been done and the effectiveness of the proposed control algorithm is verified. Tension and velocity tracking can be obtained with parameter variations.
Co-Authors Duc, Duong Minh Huong, Trinh Thi Thu Loc, Vu Gia Ly, Tong Thi Thang, Dao Duc