Optimal fuzzy PD control for a two-link robot manipulator based on stochastic fractal search

This paper focuses on the design and optimization of Fuzzy PD controllers for a two-link robot manipulator system. The dynamic equations of the two-link robot manipulator are constructed by the Lagrangian approach. The accurate motion of the robot manipulator to the desired position is implemented by fuzzy PD controllers based on the relational model and the computed torque control method. The fuzzy PD controllers are optimized by the stochastic fractal search method. The proposed control system is also evaluated by comparison with some different systems in the literature such as the genetic algorithm (GA) and the modified neural network algorithm (MNNA) with PID controllers, where its abilities are demonstrated. Numerical simulations are implemented in Matlab using the classical fourth-order Runge-Kutta method to approximate the solution of the initial-value problem. The results have shown advantages of the proposed optimal fuzzy PD controllers in terms of performance such as small error, rapid response, and high stability.