Robust Adaptive Fault-Tolerant Tracking for a Class of Mechanical Systems with Output Constraints
REN Shiji
SUN Zongyao
ZHAO Junsheng
Abstract：This paper investigates the issue of robust adaptive fault-tolerant tracking control for a class of mechanical systems with output constraints.With the aid of the dynamic surface control(DSC)technolo-gy and scaling time-varying functions,a state feedback controller based on neural networks is presented.In the presence of unmatched disturbances and non-affine nonlinear actuator faults,the controller ensures that the system satisfies the predetermined time-varying output constraints and the tracking error enters any predetermined small neighborhood of the origin before the predetermined time,while solving the prob-lem that virtual controllers need to be differentiated many times in traditional backstepping methods.The innovation lies in relaxing the requirement for the time-varying constraint functions and clarifying the logi-cal relationship between the compactness of neural networks approximation and the boundedness of closed-loop signals in the presence of time-varying factors.Finally,the simulation is provided to demonstrate the efficiency of the proposed method.
Keywords：robust adaptiveactuator faultsoutput constraintsneural networks
Publication Date：2024-10-28
Online Publishing Date：2026-08-28(First online date of this platform, not the publication date of the document)
Pages：10( 8-17 )