| Title |
Experimental Study on a Monte Carlo-based Recursive Least Square Method for System Identification |
| Authors |
이상덕(Sang-Deok Lee) ; 정슬(Seul Jung) |
| DOI |
http://doi.org/10.5370/KIEE.2018.67.2.248 |
| Keywords |
Recursive least square ; Monte carlo simulation ; inverse model identification ; Control moment gyroscope |
| Abstract |
In this paper, a Monte Carlo-based Recursive Least Square(MC-RLS) method is presented to directly identify the inverse model of the dynamical system. Although a RLS method has been used for the identification based on the deterministic data in the closed loop controlled form, it would be better for RLS to identify the model with random data. In addition, the inverse model obtained by inverting the identified forward model may not work properly. Therefore, MC-RLS can be used for the inverse model identification without proceeding a numerical inversion of an identified forward model. The performance of the proposed method is verified through experimental studies on a control moment gyroscope. |