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Active Magnetic Bearing system (AMB) is a nonlinear mechatronic device utilized for levitating the rotating components of a machine without physical contact with the stationary parts. The nonlinearity properties pose a challenge for ensuring system stability. To achieve stable and optimal performance, controllers must be incorporated. A model of the proposed AMB has been derived and results a 2X2 MIMO system. To simplify it, the model is linearized using Taylor series expansion technique. Simulation experiments have been conducted using MATLAB. In this paper, a neuro-fuzzy sliding mode controller (NFSMC) has been designed to control the position of the AMB system. Simulink models of the AMB with different control strategies have been developed for conducting simulation studies. The comparison results indicate that, with SMC, the position of the rotors follows the reference input but it is affected by chattering. It is further observed that FSMC reduces the chattering, while NFSMC controllers automatically eliminate the chattering problem and operate more robustly and smoothly. The system&#x2019;s stability has been analyzed using the Lyapunov theorem. According to the results gained, the NFSMC improves the overall system performance. The NFSMC controller yields an optimal result having no overshoot, a settling time of 0.5 sec, and a rise time of 0.10 sec in comparison with FSMC controller which exhibits overshoot of 0.392%, a settling time of 0.75 sec, and a rise time of 0.133 sec, while the SMC shows overshoot of 9.047%, a settling time of 7.5 sec, and a rise time of 0.17 sec.

Design of Neuro Fuzzy Sliding Mode Controller for Active Magnetic Bearing Control System