Fractional-order dynamics and adaptive dynamic surface control of flexible-joint robots

This paper establishes a novel fractional-order model for n-links flexible-joint (FJ) robots and proposes an adaptive dynamic surface control (DSC) scheme to address the tracking control problem. The fractional-order FJ model is built by fractional-order viscoelastic dynamics model to have a more concise form. An adaptive DSC strategy is proposed to address the tracking control problem based on backstepping method. By selecting the appropriate orders for fractional filters, the controller could solve the “explosion of complexity” problem. The unknown nonlinearities of FJ robot systems are approximated by Radial basis function (RBF) neural networks (NNs). Based on the Lyapunov stability theory, the bounds of all signals in the closed-loop system are achieved. The simulation results confirm the effectiveness of the presented control scheme.