Neural Network-based Adaptive Control of a Two-link Flexible Manipulator

This paper describes a hybrid approach to the problem of controlling flexible link manipulators for both structured and unstructured uncertainties conditions. First, a neural network controller based on the robot’s dynamic equation of motion is elaborated. It aims to produce a fast and stable control of the joint position and velocity, and to damp the vibration of each arm. Then, an adaptive neural controller is added to compensate the unknown nonlinearities and unmodeled dynamics, thus enhancing the accuracy of the control. The robustness of the adaptive neural controller has been tested under disturbances and compared to a classical nonlinear controller. Simulation results showed the effectiveness of the proposed control strategy.