Design Serial Intelligent Modified Feedback Linearization like Controller with Application to Spherical Motor
Author(s) -
Ali Barzegar,
Farzin Piltan,
Mahmood Vosoogh,
Abdol Majid Mirshekaran,
Alireza Siahbazi
Publication year - 2014
Publication title -
international journal of information technology and computer science
Language(s) - English
Resource type - Journals
eISSN - 2074-9015
pISSN - 2074-9007
DOI - 10.5815/ijitcs.2014.05.10
Subject(s) - control theory (sociology) , feedback linearization , robustness (evolution) , fuzzy logic , linearization , computer science , nonlinear system , control engineering , fuzzy control system , engineering , control (management) , artificial intelligence , physics , quantum mechanics , biochemistry , chemistry , gene
Fuzzy logic controller (FLC) is an important nonlinear controller in an uncertain dynamic system’s parameters. This controller is used to control of nonlinear dynamic systems particularly for spherical motor, because it has a suitable control performance and it is a stable. Conversely pure fuzzy logic controller is a high-quality intelligent nonlinear controller; it has two important problems; reliability and robustness in uncertain dynamic parameter. To increase the reliability and robustness, this research is focused on applied feedback linearization method in pure fuzzy logic controller. In this research the nonlinear equivalent dynamic (equivalent part) formulation problem in uncertain condition is also solved by combine pure fuzzy logic control and feedback linearization method. In this method feedback linearization theorem is applied to fuzzy logic controller to increase the stability, reliability and robustness, which it is based on nonlinear dynamic formulation. To achieve this goal, the dynamic-based formulation feedback linearization method is design. This method is robust and model-based nonlinear control therefore can reduce the nonlinearity term of system and reduce the effect of coupling. In this research MAMDANI fuzzy inference system is used as a main controller. It has minimum rule base to practical implementation. This technique was employed to obtain the desired control behavior with a number of information about dynamic model of system and a feedback linearization control was applied to reinforce system performance
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