Open AccessDesign Intelligent Model base Online Tuning Methodology for Nonlinear System
Author(s) -
Ali Roshanzamir,
Farzin Piltan,
Narges Gholami Mozafari,
Azita Yazdanpanah,
Marjan Mirshekari
Publication year - 2014
Publication title -
international journal of modern education and computer science
Language(s) - English
Resource type - Journals
eISSN - 2075-017X
pISSN - 2075-0161
DOI - 10.5815/ijmecs.2014.04.07
Subject(s) - pid controller , computer science , fuzzy logic , control theory (sociology) , control engineering , matlab , nonlinear system , controller (irrigation) , control system , base (topology) , control (management) , artificial intelligence , temperature control , engineering , mathematics , mathematical analysis , agronomy , electrical engineering , quantum mechanics , biology , operating system , physics
In various dynamic parameters systems that need to be training on-line adaptive control methodology is used. In this paper fuzzy model-base adaptive methodology is used to tune the linear Proportional Integral Derivative (PID) controller. The main objectives in any systems are; stability, robust and reliability. However PID controller is used in many applications but it has many challenges to control of continuum robot. To solve these problems nonlinear adaptive methodology based on model base fuzzy logic is used. This research is used to reduce or eliminate the PID controller problems based on model reference fuzzy logic theory to control of flexible robot manipulator system and testing of the quality of process control in the simulation environment of MATLAB/SIMULINK Simulator.
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