Design of Fractional–PID Controller Based on Grey Wolf Optimization for Robotic Manipulator

To overcome the tracking issue with robot manipulators, a modern control strategy is suggested. In this method, the system, controlled by a Fractional-order PID controller strategy, is initially modeled using information that is only partially known. A wolf grey optimization has been used to find the optimum time response, fine-tuning for variable parameter gains, which are then added to the resultant controller to approximate the ignored dynamics and modeling flaws. The suggested method is systematic and draws on principles of stabilizing joint control from well-known nonlinear dynamics. In the final step, the simulation results were acceptable and compared with several control strategies. The results obtained a superior response with a minimum execution time compared to others. FOPID based on GWO is introduced to derive the adaptation laws for variable good parameters. Computer simulation using the PUMAROBOT 560 (PR560) has been employed to demonstrate the effectiveness of the proposed controller.