4.7 Article

Stabilization of Nonlinear Vibration of a Fractional-Order Arch MEMS Resonator Using a New Disturbance-Observer-Based Finite-Time Sliding Mode Control

Journal

MATHEMATICS
Volume 11, Issue 4, Pages -

Publisher

MDPI
DOI: 10.3390/math11040978

Keywords

fractional calculus; MEMS resonator; arch beam; chaos; finite-time disturbance observer; terminal sliding mode control

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This paper discusses chaos control in an arch microelectromechanical system (MEMS) using fractional calculus. A novel disturbance-observer-based terminal sliding mode control technique is proposed to stabilize and control chaos in a fractional-order arch MEMS resonator. The design takes into account uncertainty, disturbances, and control input saturation. The effectiveness and robustness of the proposed control technique are demonstrated through numerical simulations.
This paper deals with chaos control in an arch microelectromechanical system (MEMS) from the fractional calculus perspective. There is a growing need for effective controllers in various technological fields, and it is important to consider disruptions, uncertainties, and control input limitations when designing a practical controller. To address this problem, we propose a novel disturbance-observer-based terminal sliding mode control technique for stabilizing and controlling chaos in a fractional-order arch MEMS resonator. The design of this technique takes into account uncertainty, disturbances, and control input saturation in the fractional-order system. The proposed control technique is practical for real-world applications because it includes control input saturation. The equation for a fractional-order arch MEMS resonator is presented, and its nonlinear vibration and chaotic behavior are studied. The design process for the proposed control technique is then described. The Lyapunov stability theorem is used to prove the finite-time convergence of the proposed controller and disturbance observer. The proposed controller is applied to the arch MEMS resonator, and numerical simulations are used to demonstrate its effectiveness and robustness for uncertain nonlinear systems. The results of these simulations clearly show the effectiveness of the proposed control technique.

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