Open AccessCoast function parameters optimization for DC battery source inverter feeding three-phase inductive load
Author(s) -
Riyadh G. Omar
Publication year - 2020
Publication title -
international journal of power electronics and drive systems/international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
eISSN - 2722-2578
pISSN - 2722-256X
DOI - 10.11591/ijpeds.v11.i4.pp1799-1804
Subject(s) - control theory (sociology) , inverter , computer science , harmonics , approximation error , function (biology) , mean squared error , algorithm , voltage , control (management) , mathematics , statistics , engineering , artificial intelligence , evolutionary biology , electrical engineering , biology
The commonly reported measures of the predictive accuracy are evaluated in this paper. Absolute, squared, percentage, and integral errors methods are implemented, to reduce the objective function, which employed in model predictive control. These methods are usually investigated for dc source inverter, which controlled by finite set model predictive current control system, with three phase induction motor load. In this paper, the evaluation includes different aspects, accuracy, complexity, system harmonics content, and execution time. A vital criterion in this process is the performance of the inverter, and the matching between the reference and the measured machine currents. The evaluation shows that for one term objective function, absolute and square errors give similar results with less execution time for the absolute error, but if multi terms objective function the square error is better.