Open AccessRobust Control with Genetic Algorithms of a Permanent Magnet Synchronous Machine Driving an Elastic Load Variable Inertia
Author(s) -
Sunny Lee
Publication year - 2015
Publication title -
modern applied science
Language(s) - English
Resource type - Journals
eISSN - 1913-1852
pISSN - 1913-1844
DOI - 10.5539/mas.v10n1p1
Subject(s) - control theory (sociology) , inertia , computer science , variable (mathematics) , matlab , pid controller , controller (irrigation) , simple (philosophy) , bang–bang control , algorithm , optimal control , control (management) , control engineering , mathematics , mathematical optimization , artificial intelligence , engineering , temperature control , mathematical analysis , agronomy , philosophy , physics , epistemology , classical mechanics , biology , operating system
The goal of this work is to contribute to the conception rules of the synthesis law control in order to give them a robust character. We study the issue of controlling of the synchronous motor driving a mechanical load. This load, driven by an elastic joint, presents a variable and bounded inertia. The synthesis of simple correctives and methods of the best corrective in the parameter variation interval are presented. In this paper, the synthesis rules of a PID regulator on which we added an optimization iterative method based on the system behavior expertise and genetic algorithm. This phase made it possible to give simple rules of synthesis and the parameterization of optimization method so as to find the three optimal degrees of correction freedom. The results are validated by simulation by means of MATLAB Simulink and present a better dynamic performance of the proposed control law.