Adaptive prescribed-time disturbance observer using nonsingular terminal sliding mode control: Extended Kalman filter and particle swarm optimization
Amin Vahidi-Moghaddam, Arman Rajaei, Moosa Ayati, Ramin Vatankhah,, Mohammad Reza Hairi-Yazdi

TL;DR
This paper presents an adaptive control scheme combining a prescribed-time disturbance observer, nonsingular terminal sliding mode control, Extended Kalman Filter, and particle swarm optimization to achieve finite-time stabilization of uncertain nonlinear systems, demonstrated on nanobeam vibration.
Contribution
It introduces a novel integrated approach using EKF and PSO for real-time estimation and parameter tuning in prescribed-time control of nonlinear systems with disturbances and input saturation.
Findings
Effective finite-time stabilization of nanobeam vibrations.
Enhanced disturbance rejection and parameter estimation accuracy.
Superior performance compared to conventional sliding mode control.
Abstract
In this paper, adaptive prescribed finite time stabilization of uncertain single-input and single-output nonlinear systems is considered in the presence of unknown states, unknown parameters, external load disturbance, and non-symmetric input saturation. A prescribed finite time disturbance observer is designed to approximate the unmeasured external disturbance. Also, a nonsingular prescribed finite time terminal sliding mode control is proposed for the closed-loop control of the system with the non-symmetric input saturation. Extended Kalman filter algorithm is employed for the real-time estimations of the states and unknown parameters of the system. Moreover, particle swarm optimization algorithm is used to obtain the design parameters of the proposed disturbance observer and controller. To show the performance of designed control scheme, the proposed approach is employed to guarantee…
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