Condition Monitoring Leading to Control by Using Fuzzy and Hybrid Fuzzy Models: A Review
Darshan Singh1, Dalveer Kaur2, Yaduvir Singh3
1Prof. Darshan Singh,  Assistant Professor, Department of Electronics and Communication Engineering at GZSCET Bhatimda Punjab, India.
2Prof Dalveer Kaur,  Assistant Professor, Department of Electronics and Communication Engineering at PTU Kapurthala, Punjab, India.
3Prof. Yaduvir Singh, Director of  NIET at Greater Noida, (U.P) India.
Manuscript received on November 19, 2012. | Revised Manuscript received on December 16, 2012. | Manuscript published on December 30, 2012. | PP:199-206| Volume-2, Issue-2, December 2012.  | Retrieval Number: B0841112212 /2012©BEIESP

Open Access | Ethics and Policies | Cite
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Plant wide control is a major area of research in current days and application of artificial intelligence techniques provide better results from conventional methods in control applications. In majority of the cases, researchers got much better results when they applied artificial intelligence algorithms in various engineering problems. Engineering problems have shown remarkable enhancement in performance and also efficiency when different artificial intelligence techniques were applied in comparison to conventional techniques. There are three basic domains in artificial intelligence viz. fuzzy logic, artificial neural network and optimization techniques. This paper reports the various research contributions made into condition monitoring aspects of induction motor using fuzzy logic and neuro-fuzzy logic (hybrid fuzzy). 
Keywords: Artificial Intelligence, Condition monitoring, Fuzzy logic, Neuro-fuzzy logic.