Command Filter-Based Prescribed Performance Adaptive Control for Fractional Order Non-Strict System With Unmodeled Dynamics and Input Delay

Abstract

This article focuses on adaptive control of a class of non-strict feedback nonlinear fractional order systems with input delay and unmodeled dynamics under prescribed performance constraints. Command filtering backstepping design method is employed to avoid explosion of computation. Additionally, an error compensation mechanism is established to mitigate any errors introduced by the command filter. Radial basis function neural network is utilized to approximate the nonlinear function. Auxiliary signal processing variables are introduced to handle unmodeled dynamics. To address the input delay problem, a Pade approximation technique is employed. The stability analysis of the controller is conducted using Lyapunov stability theory, ensuring that the tracking error converges within a narrow predefined performance range. Finally, simulation results are presented to demonstrate the effectiveness of the proposed controller.