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Controlling the Pitch and Yaw Angles of a 2-DOF Helicopter Using Interval Type-2 Fuzzy Neural Networks

  • Chapter
Recent Advances in Sliding Modes: From Control to Intelligent Mechatronics

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 24))

Abstract

Due to not only having strong nonlinear inter-couplings in its model but also being an open-loop unstable system, control of a 2-degree of freedom (DOF) helicopter is a challenging task. This chapter deals with the decentralized control of the Quanser 2-DOF helicopter system by designing an interval type-2 fuzzy neural network for the control of the pitch and yaw angles by using a sliding mode control theory-based training algorithm. The proposed control method is known as feedback error learning in which an intelligent controller, a type-2 fuzzy neural network in this case, works in parallel with a conventional PD controller. In the proposed scheme, on one hand, the conventional PD controller is responsible to maintain the stability of the system until the intelligent controller takes the responsibility of controlling the system. On the other hand, the intelligent controller learns the system dynamics online with a sliding mode control-theory based learning algorithm. The simulation results show that without having neither a priori knowledge about the mathematical model of the system nor its parameters, the proposed control algorithm is able to track the reference signals for both yaw and pitch angles without giving a steady state error. In addition, the simulation results show the superiority of the proposed control scheme over its type-1 counterpart in the presence of noise in the system. In addition to its robustness, the sliding mode control theory-based learning algorithm has additional advantages such as having no matrix manipulations or partial derivatives which makes the overall training and control algorithm computationally simple and fast when compared to other methods, e.g. gradient-descent based methods.

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Author information

Authors and Affiliations

  1. Department of Electrical and Control Engineering, Faculty of Electrical and Computer Engineering, Semnan University, Semnan, 35131, Iran

    Mojtaba Ahmadieh Khanesar

  2. School of Mechanical & Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, Singapore, 639798

    Erdal Kayacan

Authors
  1. Mojtaba Ahmadieh Khanesar
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  2. Erdal Kayacan
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Correspondence to Mojtaba Ahmadieh Khanesar .

Editor information

Editors and Affiliations

  1. RMIT University, Carlton, Victoria, Victoria, Australia

    Xinghuo Yu

  2. Hacettepe University, Beytepe, Ankara, Turkey

    Mehmet Önder Efe

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Khanesar, M.A., Kayacan, E. (2015). Controlling the Pitch and Yaw Angles of a 2-DOF Helicopter Using Interval Type-2 Fuzzy Neural Networks. In: Yu, X., Önder Efe, M. (eds) Recent Advances in Sliding Modes: From Control to Intelligent Mechatronics. Studies in Systems, Decision and Control, vol 24. Springer, Cham. https://doi.org/10.1007/978-3-319-18290-2_17

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  • DOI: https://doi.org/10.1007/978-3-319-18290-2_17

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18289-6

  • Online ISBN: 978-3-319-18290-2

  • eBook Packages: EngineeringEngineering (R0)

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