Adaptive Barrier Control for Nonlinear Servomechanisms with Friction Compensation

Abstract EN

This paper proposes an adaptive barrier controller for servomechanisms with friction compensation.

A modified LuGre model is used to capture friction dynamics of servomechanisms.

This model is incorporated into an augmented neural network (NN) to account for the unknown nonlinearities.

Moreover, a barrier Lyapunov function (BLF) is utilized to each step in a backstepping design procedure.

Then, a novel adaptive control method is well suggested to ensure that the full-state constraints are within the given boundary.

The stability of the closed-loop control system is proved using Lyapunov stability theory.

Comparative experiments on a turntable servomechanism confirm the effectiveness of the devised control method.