Adaptive Neural Funnel Control for Nonlinear Two-Inertia Servo Mechanisms With Backlash

This paper proposes a modified adaptive neural control algorithm with a funnel function for nonlinear two-inertia servomechanisms with backlash and external disturbance. A continuous tracking differentiator is employed to replace the first-order filter in the traditional dynamic surface control design. A novel funnel function is employed and used in control design to improve the control performance. Then, an adaptive neural dynamic surface controller based on funnel control is presented to guarantee the tracking performance of two-inertia servomechanisms. In addition, the unknown dynamics, including backlash, nonlinear friction, and external disturbance, are approximated by using the echo state neural network and compensated online. The comparative experimental results validate the effectiveness of the developed control algorithm based on a two-inertia servo mechanism.