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This is a Experimental Study study.

Reduced-order observer-based robust trajectory tracking control of MAV quadrotor with disturbances

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Control algorithm improves trajectory tracking in quadrotors, reducing computational demand while rejecting disturbances.

The control algorithm effectively integrates a sliding mode controller with a nonlinear disturbance observer.
Findings reveal enhanced trajectory tracking for quadrotors by estimating output rates from position and attitude alone.
A reduced-order observer design minimizes computational power while estimating state variables accurately.
The nonlinear disturbance observer attenuates various disturbances without needing prior knowledge of their characteristics.

Rasool et al. (2025) studied this question.

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View Full Paper

Ask AI

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Authors

Control algorithm improves trajectory tracking in quadrotors, reducing computational demand while rejecting disturbances.

The control algorithm effectively integrates a sliding mode controller with a nonlinear disturbance observer.
Findings reveal enhanced trajectory tracking for quadrotors by estimating output rates from position and attitude alone.
A reduced-order observer design minimizes computational power while estimating state variables accurately.
The nonlinear disturbance observer attenuates various disturbances without needing prior knowledge of their characteristics.

Rasool et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark