Multiscale Chebyshev Neural Network Identification and Adaptive Control for Backlash-Like Hysteresis System

Abstract EN

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.