Modified Grey-Wolf Algorithm Optimized Fractional-Order Sliding Mode Control for Unknown Manipulators With a Fractional-Order Disturbance Observer

摘要

This paper studies a new fractional-order nonsingular terminal sliding mode control (FTSMC), in which all parameters of controller and observer are optimized by a modified grey wolf optimization (MGWO) technique for robotic manipulator systems. Based on an improved fractional-order terminal sliding surface, the new FTSMC system is designed and the unknown disturbance is estimated by a fractional-order finite-time disturbance observer. The dynamic parameters of manipulator and gains of the controller were optimized with the help of the newly developed MGWO technique via both off-line simulation and on-line experimental optimization learning process. Simulation and experimental results of MGWO optimization and joint positioning for a self-designed manipulator showed the efficacy of the proposed optimization and control schemes.