Design of Adaptive Controller for Robot Arm Manipulator Based on ANN with Optimized PID by IWO Algorithm

In this paper, a robot motion control system is adaptive controller based on the artificial Neural Network optimized PID by IWO. A proposed method for solving reverse kinematics used to determine the angle values of the arm joints when traced in any path. Forward kinematics derived according to the D-H method (Devavit - Hartenberg) representation. The design of the dynamic model based on the Lagrange method. Computing the dynamic model is a very important step in the robotics world. The adaptive controller based on ANN optimized PID used to improve system response. We can compute the forward kinematics and reverse kinematics and trajectory planning by design a graphical user interface by using MATLAB, computing the forward and reverse kinematics by hand is not easy, so by using this design it is an easier way. The dynamic model used with the adaptive controller based on ANN optimized PID, this method tries to select the PID parameters, without needing to the robot manipulator mathematical model. The system performance results show better response when using the proposed controller, the maximum overshot is equal to zero and the raise time is reduced to 0.1 in joint 3 also the optimal settling time 0.2 in joint 1 the delay time is reduced to 0.1 in joint 1 and joint 5. These results are much better when compared with traditional methods such as traditional PID controller. This proposed algorithm improved the system parameters to the optimal values.