Adaptive Fixed-Time Control for an Uncertain Two-Link Flexible Robot with Constraints

Abstract

For the trajectory tracking and vibration suppression of a two-link flexible robot, a neural networksbased fixed-time control method is proposed, which takes into account the system uncertainty, output constraint and input saturation. Novel adaptive law and virtual control are designed for the solution of the system uncertainty in the fixed-time convergence settings. The barrier Lyapunov function (BLF) is used to solve the output constraint problem of the system. Furthermore, control chattering is discussed in detail. In the end, through the simulation, we present the control performance of the proposed fixed-time control method.