Adaptive Neural Network Control of Two-DOF Robotic Arm driven by Electro-hydraulic Actuator with Output Constraint

Abstract

In this paper, an adaptive neural network (ANN) control is presented for a two degree of freedom robotic arm driven by electro-hydraulic actuator (EHA) with output constraints. ANN control is used to estimate the unknown model of a manipulator. A backstepping controller is designed, which ensures the stability of system and satisfies the dynamic tracking performance of EHA, where the convergence of closed loop system is strictly proved by Lyapunov method. Using the control method proposed in this paper, the signals are semi globally uniformly bounded in the closed-loop system, and the output constraints are not violated. The effectiveness of the presented controller is verified in the two degree of freedom robotic arm by the simulation results.