Mamdani-based fuzzy logic controller for travel angle control of bench-top helicopter

Bench-top helicopter with 3 Degree of freedom is developed by the Quanser Inc. It is a small-scale helicopter that is used as testing bench for the real helicopter. The bench-top helicopter has the same behavior as the real helicopter and usually used by scientists and engineers to test their contro...

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Bibliographic Details
Main Authors: Mat Esa, Mohamad Khairul Azmi, Mansor, Hasmah, Gunawan, Teddy Surya, Janin, Zuriati
Format: Conference or Workshop Item
Language:English
English
Published: Institute of Electrical and Electronics Engineers Inc. 2019
Subjects:
Online Access:http://irep.iium.edu.my/71681/1/71681_Mamdani-based%20Fuzzy.pdf
http://irep.iium.edu.my/71681/7/71681%20Mamdani-based%20Fuzzy%20Logic%20Controller%20SCOPUS.pdf
http://irep.iium.edu.my/71681/
https://ieeexplore.ieee.org/document/8688807
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Summary:Bench-top helicopter with 3 Degree of freedom is developed by the Quanser Inc. It is a small-scale helicopter that is used as testing bench for the real helicopter. The bench-top helicopter has the same behavior as the real helicopter and usually used by scientists and engineers to test their controllers before applying to the real helicopter. The bench-top helicopter is mounted with two rotor that depends on the voltage supplied to it to change the direction. The movement of the helicopter is based on the direction of three-different angles; pitch, travel and yaw angles. A Linear Quadratic Regulator-Integral controller, developed by Quanser is the existing controller that is used to control those three angles of the bench-top helicopter. The main objective of this project is to develop Mamdani-based Fuzzy Logic Controller for travel angle control of bench-top helicopter and compare controller response performance with the existing LQR-I Controller. Thus, Fuzzy Logic Controller has been proposed to replace the existing controller to increase the efficiency of the of the bench-top helicopter performance. Several simulation works have been done to test the Fuzzy Logic Controller performance so that it will produce output response as close to the desired output. Performance comparisons have been done between Fuzzy Logic and LQR-I. At the final stage of the test, the Fuzzy Logic Controller has been applied to the actual hardware. From the results, it can be concluded that the response performance of Fuzzy Logic Controller is better than LQR-I Controller especially for closed-loop simulation at desired angle 30°, the percentage of overshoot/settling time of the Fuzzy Logic Controller is 4.912% whereas the LQR is 7.002%.