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Stabilization and Control of Elastic Inverted Pendulum System (EIPS) Using Adaptive Fuzzy Inference Controllers

Stabilization and Control of Elastic Inverted Pendulum System (EIPS) Using Adaptive Fuzzy Inference Controllers

Ashwani Kharola, Pravin P. Patil
Copyright: © 2017 |Volume: 6 |Issue: 4 |Pages: 12
ISSN: 2156-177X|EISSN: 2156-1761|EISBN13: 9781522514961|DOI: 10.4018/IJFSA.2017100102
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MLA

Kharola, Ashwani, and Pravin P. Patil. "Stabilization and Control of Elastic Inverted Pendulum System (EIPS) Using Adaptive Fuzzy Inference Controllers." IJFSA vol.6, no.4 2017: pp.21-32. http://doi.org/10.4018/IJFSA.2017100102

APA

Kharola, A. & Patil, P. P. (2017). Stabilization and Control of Elastic Inverted Pendulum System (EIPS) Using Adaptive Fuzzy Inference Controllers. International Journal of Fuzzy System Applications (IJFSA), 6(4), 21-32. http://doi.org/10.4018/IJFSA.2017100102

Chicago

Kharola, Ashwani, and Pravin P. Patil. "Stabilization and Control of Elastic Inverted Pendulum System (EIPS) Using Adaptive Fuzzy Inference Controllers," International Journal of Fuzzy System Applications (IJFSA) 6, no.4: 21-32. http://doi.org/10.4018/IJFSA.2017100102

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Abstract

Elastic Inverted Pendulum system (EIP) are very popular objects of theoretical investigation and experimentation in field of control engineering. The system becomes highly nonlinear and complex due to transverse displacement of elastic pole or pendulum. This paper presents a comparison study for control of EIP using fuzzy and hybrid adaptive neuro fuzzy inference system (ANFIS) controllers. Initially a fuzzy controller was designed, which was used for training and tuning of ANFIS controller using gbell shape membership functions (MFs). The performance of complete system was evaluated through output responses of settling time, steady state error and maximum overshoot. The study also highlights effect of varying number of MFs on training error of ANFIS. The results showed better performance of ANFIS controller compared to fuzzy controller.

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