Open AccessParameter Estimation of a dc Motor-Gear-ac Generator Mathematical Model
Author(s) -
Paul Kiplimo Tarus,
Wesley Koech
Publication year - 2021
Publication title -
journal of advances in mathematics and computer science
Language(s) - English
Resource type - Journals
ISSN - 2456-9968
DOI - 10.9734/jamcs/2021/v36i1030408
Subject(s) - matlab , control theory (sociology) , block (permutation group theory) , generator (circuit theory) , dc motor , gradient descent , computer science , mathematical model , nonlinear system , control engineering , engineering , mathematics , power (physics) , artificial neural network , artificial intelligence , electrical engineering , physics , statistics , geometry , control (management) , quantum mechanics , operating system
Mathematical models and there parameters are essential for designers to predict the close loop behaviors of the plant so that systems are stable. A block model is develop in the MATLAB/simulink for the DC Motor-Gear-AC-Generator mathematical model in this paper, the block built is used to estimate the parameters in the estimation node using the gradient descent, simplex search and nonlinear least square algorithm. Gradient descent curve match that of the experimental data and its values are used in the DC Motor-Gear-AC Generator mathematical model.
Objective:
To built block simulink
Estimate the parameters of the DC Motor-Gear-Generator mathematical model.