Tuning of SMC Parameters for Robotic Manipulator Based on Whale Optimization Algorithm

A 2-link robotic manipulator is selected as a research instance, a sliding mode control(SMC) law is designed. Parameters tuning of sliding mode controller is converted to a nonlinear optimization problem with the objects of minimizing the trajectory tracking error and eliminating chattering of the control torques. The whale optimization algorithm (WOA) is adopted in this paper to obtain the best parameters of controller, and a comparative study with the results that are searched by particle swarm optimization (PSO) is made. Through simulation of the manipulator, control effects of the parameters obtained by the two optimization methods are compared. Research shows that WOA is a viable optimization method for parameter tuning of sliding mode control of robotic manipulator, and the optimization model proposed in this paper can effectively eliminate the chattering problem of control torques.