IMPLEMENTATION OF OKID-BASED SYSTEM IDENTIFICATION AND CONTROL TO A DC-MOTOR

摘要

Many open loop identification methods have been developed in the literature. In this paper, we compare some of them, especially for first and second order systems in order to benchmark the Observer Kalman Identification (OKID) method. The ultimate objective is to design an online optimal control. We proceed in different stages. First, we begin by collecting DC-motor Input and Output Data using LabView. Then, we applied several identification techniques such as: Recursive Least Squares, Weighted Recursive Least Squares, Instrumental Variable, Subspace Identification, and finally, OKID. Based on the performance obtained in the identification stage, an optimal linear quadratic Gaussian integral control is proposed and implemented.