Multiscale Chebyshev Neural Network Identification and Adaptive Control for Backlash-Like Hysteresis System. (3rd October 2018)

• Record Type: Journal Article
• Authors: Gao, Xuehui; Liu, Ruiguo
• Other Names: Yang Zhile Academic Editor.
• Is Part Of: Complexity. Volume 2018(2018)
• Publication Date: 2018-10-03
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2018/1872493
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : An adaptive control based on a new Multiscale Chebyshev Neural Network (MSCNN) identification is proposed for the backlash-like hysteresis nonlinearity system in this paper. Firstly, a MSCNN is introduced to approximate the backlash-like nonlinearity of the system, and then, the Lyapunov theorem assures the identification approach is effective. Afterward, to simplify the control design, tracking error is transformed into a scalar error with Laplace transformation. Therefore, an adaptive control strategy based on the transformed scalar error is proposed, and all the signals of the closed-loop system are uniformly ultimately bounded (UUB). Finally, simulation results have demonstrated the performance of the proposed control scheme.