Adaptive neuro-fuzzy control approach for a single inverted pendulum system
The inverted pendulum is an under-actuated and nonlinear system, which is also unstable. It is a single-input double-output system, where only one output is directly actuated. This paper investigates a single intelligent control system using an adaptive neuro-fuzzy inference system (ANFIS) to stabil...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Institute of Advanced Engineering and Science
2018
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/84653/1/HermanAbdulWahid2018_AdaptiveNeuroFuzzyControlApproachforaSingleInverted.pdf http://eprints.utm.my/id/eprint/84653/ http://dx.doi.org/10.11591/ijece.v8i5.pp3657-3665 |
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| Institution: | Universiti Teknologi Malaysia |
| Language: | English |
| Summary: | The inverted pendulum is an under-actuated and nonlinear system, which is also unstable. It is a single-input double-output system, where only one output is directly actuated. This paper investigates a single intelligent control system using an adaptive neuro-fuzzy inference system (ANFIS) to stabilize the inverted pendulum system while tracking the desired position. The non-linear inverted pendulum system was modelled and built using MATLAB Simulink. An adaptive neuro-fuzzy logic controller was implemented and its performance was compared with a Sugeno-fuzzy inference system in both simulation and real experiment. The ANFIS controller could reach its desired new destination in 1.5 s and could stabilize the entire system in 2.2 s in the simulation, while in the experiment it took 1.7 s to reach stability. Results from the simulation and experiment showed that ANFIS had better performance compared to the Sugeno-fuzzy controller as it provided faster and smoother response and much less steady-state error. |
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