Dynamic Parameter Identification Based on the Recursive Least Squares Method for a 2-DOF Manipulator Using Brushless DC Motor

Parameter identification plays an important role in ensuring the stability and efficiency of the system. In this paper, a parameter identification algorithm for robots using brushless DC (BLDC) motors is presented. Firstly, the system kinematics is modeled using parameters defined according to the Modified Denavit-Hartenberg (Modified D-H) convention, followed by the derivation of the dynamic model based on the Lagrange-Euler formulation. Then, the Recursive Least Squares (RLS) method is applied to identify dynamic parameters. Finally, the proposed method is simulated in MATLAB Simulink using a PD controller for both the estimated dynamic model and the SolidWorks - based robot model. The method's accuracy is assessed using the Root Mean Square Error (RMSE). The entire process is simulated in MATLAB/Simulink and subsequently validated through experimental verification.