Hybrid adaptive neural control for flexible manipulators

Abstract

This article describes a hybrid control strategy to deal with the problem of controlling flexible link manipulators. The motion control of a planar manipulator with two flexible arms is studied. Dynamics is developed in Lagrange's formulation. A novel control system structure is proposed to control the joint position and velocity as well as the deflection of the tip for each arm. First, a non-linear control law based on the dynamic motion equation of the robot is presented and the stability analysis is studied. Then, an adaptive neural controller is implemented to compensate errors due to structured and unstructured uncertainties. Efficiency of the new controller obtained by combining the two control laws is tested facing an important variation of the dynamic parameters of the flexible manipulator and compared to the non-linear control taken solely. Simulation results show the effectiveness of the control strategy proposed.