Time-Varying Quadratic-Programming-Based Error Redefinition Neural Network Control and Its Application to Mobile Redundant Manipulators

Abstract

By incorporating the redefined error monitor function into the network design, an error redefinition neural network (ERNN) is proposed to control mobile redundant manipulators to execute the tracking task in this article. The global asymptotic stability and the strong antidisturbance capability of the ERNN are proved theoretically. Furthermore, the ERNN can overcome the overshoot and constant disturbance. Meanwhile, the ERNN is input-to-state stable, while the bounded time-varying disturbance is considered as the control input.