Systematic Approach Towards Computer Aided Non-Linear Control System Analysis Using Describing Function Models
Machine Learning Research
Volume 4, Issue 1, March 2019, Pages: 13-20
Received: Mar. 22, 2019;
Accepted: Apr. 30, 2019;
Published: Jun. 18, 2019
Views 322 Downloads 27
Aparna Sadanand Telang, Department of Electrical Engineering, Faculty of P. R. Patil College of Engineering Management, Sant Gadgebaba Amravati University, Amravati, India
Prashant Prabhakar Bedekar, Department of Electrical Engineering, Faculty of Government College of Engineering, Gondwana University, Chandrapur, India
In recent years, control system problems involving non linearities are important concerns in the framework of automation industries. Actuators with non-linear behavior such as saturation, dead zone, relay, backlash etc. may be responsible for poor control performance in the system. The analysis of these non-linearities is an important task for a control system engineer. Moreover the methods of analyzing these non-linearities are time consuming and non-generic. This paper presents simple and systematic approach for analyzing such kind of non-linearities using user-friendly MATLAB tool “Nonlintool”. This tool saves the time as well as provides visual effects for analysis. Main contribution of this paper is to show how user friendly MATLAB tool “Nonlintool” can extensively be used for quicker and wider interpretation of results based on describing function models. The novelty of this paper lies in analyzing all kinds of non-linearities along with their impact on stability of the nonlinear system. The performance has been evaluated for varying conditions of magnitude and gain of the system as well as on various transfer function models. The results of stability analysis, for which only standard transfer function model is considered, are presented here.
Aparna Sadanand Telang,
Prashant Prabhakar Bedekar,
Systematic Approach Towards Computer Aided Non-Linear Control System Analysis Using Describing Function Models, Machine Learning Research.
Vol. 4, No. 1,
2019, pp. 13-20.
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