Implement of Intelligent Controller for 6DOF Robot Based on a Virtual Reality Model

Every designer aspires to produce designs that are superior to those of their rivals in terms of quality, speed, or efficiency. Using an ANFIS (Adaptive Neural Inference System) controller and a proportional, integrated, derived (2DO-PID) 2-degree of freedom controller, this study suggests a high-performance design for a 6-DOF manipulator. Finding the best value for the controller settings that smoothly regulate the robot's movements to the desired aim is the primary objective of this exercise. The first step in the design process is to naturally determine the best values for the parameters of a traditional PID controller. The creation of a high-resolution 2DOF-PID controller is the next phase. It performs better than the conventional correct order using a mysterious physics control technique. The parameters of the 2DOF-PID controller are estimated based on the undeniably significant nature of the control effect. The final stage in achieving the high performance of the control system under consideration is the hybrid 2DOF-PID and ANFIS controller, which uses the prior output as a predictive point. The use of both modern and vintage consoles. Six-degree-of-freedom elbow curves are supported. Because the manipulator's trajectory exceeded the settling time and affected the movement, it was possible to minimize. MATLAB 2021b and Robotics Toolbox 9 were used to design and simulate the entire remote-control system. The controller's optimal design is built using a 3-dimensional model of a 6-DOF manipulator created with MATLAB/virtual Simulink's reality (VR) technology. MATLAB generates the manipulator instructions, which are then used to generate a real trajectory with a virtual reality model.