Position control of planar three-link underactuated manipulator based on wavelet neural network model

This paper presents a control strategy for a planar three-link underactuated manipulator(UM) with a passive first link based on a wavelet neural network (WNN) model. Firstly, by using the particle swarm optimization (PSO) algorithm, the target angles of all links are calculated according to the established kinematic model and the given target position. Then, a WNN model is trained to describe the coupling relationship between the passive link and the second link. The difference between the current angle and the target angle of the passive link is converged to zero by repeatedly controlling the second link to rotate an angle which is calculated by the trained WNN model. Next, the active links are controlled to rotate to their target angles with low speeds. Finally, the effectiveness of the proposed control strategy is verified through experimental results.