Nonlinear Modeling and System Identification of a DC Gear Motor with Unknown Parameters

Modeling and identification of industrial systems is an essential stage in practical control design and applications. The paper presents linear, state space, nonlinear modeling and identification of a DC gear motor with real time experiments. The main aim of this research is to use the concept of modeling and System Identification method for observing the greater accuracy and better fitness system model, and validate it by applying various data sets of the hardware experiment. System Identification deals with the problem of building mathematical models of dynamical systems based on observed data from the systems. The methodology is based on results obtained from the simulation of theoretical concepts, which are then validated by repeating experiments on the motor. It is very important to do this validation because sometimes these theoretical concepts are not able to fully capture the nature of the physical elements, and both results may differ. Proceeding in this way, it can guarantee a greater extent that the results are correct. Htet Htet Shin | Nay Min Tun "Nonlinear Modeling and System Identification of a DC Gear Motor with Unknown Parameters" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26475.pdfPaper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/26475/nonlinear-modeling-and-system-identification-of-a-dc-gear-motor-with-unknown-parameters/htet-htet-shin