Design and implementation of interval type-2 single input fuzzy logic controller for magnetic levitation system

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Abstract

This paper deals with the design and implementation of an interval type-2 single input fuzzy logic controller (IT2SIFLC) for a Magnetic Levitation System (MLS). The type-2 fuzzy controller is designed in such a way that it can be implemented with signed distance method. With help of signed distance, interval type-2 fuzzy input variable in our simple fuzzy logic controller called type-2 single input FLC. This research work is mainly focused on suspending the steel ball without any mechanical support in desired position with help of an efficient controller which uses less number of rules and less processor's time complexity. For this task we have proposed an interval type-2 single input fuzzy logic controller (IT2SIFLC) based on theory of type-2 fuzzy logic systems (T2FLS) and single input theory of fuzzy logic control. Which has the advantage of the total number of rules are abruptly reduced compared to IT2FLC. Fuzzy logic based on interval value sets is capable of modelling the uncertainty and precision in a better way. However, in real time application uncertainty associated with the available information is always occurs. The proposed controller performance is compared with the conventional fuzzy logic controller i.e. type-1 fuzzy logic controller (T1FLC), IT2FLC controller designed with the help of interval type-2 fuzzy inference system toolbox in the MATLAB-Simulink environment. Simulation results show that the proposed controller is fast with high degree of uncertainty. Simulation results analysed for all the controllers and validated in the real time model of the MLS. The proposed IT2SIFLC is surpassing the performance obtained with other controllers and is cleared from the computed time response parameters. © 2013 Springer.

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Kumar, A., Panda, M. K., & Kumar, V. (2013). Design and implementation of interval type-2 single input fuzzy logic controller for magnetic levitation system. In Advances in Intelligent Systems and Computing (Vol. 174 AISC, pp. 833–840). Springer Verlag. https://doi.org/10.1007/978-81-322-0740-5_99

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