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Machine Learning Bouc-Wen Model for Nano- positioning System

Sumitha C, Anandaraju M B

Abstract


Most of the application in present world has taken ‘Nano’ as a part of their near future implementation. In Nano-Positioning System (NPS) the mechanical dynamics are handled at Nano scale. Designing a precisioned NPS is a greater challenge. To have a better hysteresis and better behaviour (Static/Dynamic) the Bouc-Wen model is modified by linearizing. In this work SISO (Sıngle-input Sıngle-Output) and MIMO (Multiple-Input Multiple-Output) models of NPS are designed. In most of the previous work, conventional system were treated at macro level. This work inclines the work to NPS. Sustainable results were possible using Kalman Filter in NPS. The entire system is modelled in MATLAB/Simulink and checked across 3 sorts of electrical signals. Each design is compared using various performance parameters. Machine learning process is included to suggest the appropriate voltage levels among various voltage levels.


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DOI: https://doi.org/10.37628/ijan.v9i1.984

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