Tracking Performance Of Maglev System Using Type-2 Fuzzy Logic Control

Interval Type-2 Fuzzy Logic Controller (IT2FLC), Interval Type-2 SIFLC, Interval Type-2 Fuzzy Sliding Mode Controller
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Currently, he is pursuing his M.Tech in System modeling and control from Indian institute of technology Roorkee, India. He has done extensive research work in the field of control of Magnetic Levitation System (MLS). His current area of research includes Fuzzy Control, Soft Computing techniques and its applications in Control System.
This research work is mainly focused on suspending the steel ball without any mechanical support in desired position and how the Magnetic Levitation System works in presence of disturbance with help of an efficient controller.The tracking performance and robustness is also checked for this system. For tracking, two type of reference trajectory are modelled. One is sine wave and other is a set of constant point varying at different levels. Lastly for robust performance, disturbance is applied in MLS.For this task we have designed Interval Type-2 Fuzzy Logic Controller (IT2FLC), Interval Type-2 Single Input Fuzzy Logic Controller (IT2SIFLC), Interval Type-2 Fuzzy Sliding Mode Controller (IT2FSMC) based on theory of type-2 fuzzy logic systems. Uncertainty is an inherent part of intelligent systems used in real world applications. Conventional controllers can not fully handle the uncertainties present in real-time systems. Type-2 fuzzy sets that are used in type-2 fuzzy systems can handle such uncertainties in a better way because they provide us an extra degree of freedom. At last The designed controller s performance is compared with the feedback linearization control.

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