Comparison of Parameter Estimation Techniques for Control Parameter Identification of Permanent Magnet Direct Current Motor Speed Control

Abstract

The proportional-integral-derivative (PID) controller is an important digital control structure that is frequently used by designers in many speed, position, and temperature applications. The main problem of such control structures is that the mathematical calculation burden is high and requires precise parameter determination. In this study, the control parameters were estimated to overcome the two main problems given above for the speed control of a Permanent Magnet Direct Current (PMDC) motor produced in real time. For this process, the Nonlinear Least Squares (NLS) optimization method with the Trust-Region-Reflective (TRR) algorithm, the Pattern Search (PS) optimization method with the Active-Set (AS) algorithm, and the Simplex Search (SS) optimization method with the AS algorithm have been proposed. The proposed techniques are explained in detail, and the Sum of Square Error (SSE) is chosen as the objective function for these techniques. The predicted controller values for a single reference were tested under different speed, load, and armature resistance conditions. The speed control of the PMDC motor, which was created using the parameters estimated over the specified simulation periods, was tested with different load conditions. According to the results obtained, while the NLS-TRR technique stands out in terms of calculation time, the SS-AS technique outperformed in terms of precise parameter estimation.