Preconditioned Performance Trajectory Tracking Control of a Dynamic Adaptive Sliding Mode Observer for Quadrotor UAV

  • Qiu Xu Yangzhou Polytechnic Institute, Yangzhou 225127, Jiangsu, China
  • Li Zhang Yangzhou Polytechnic Institute, Yangzhou 225127, Jiangsu, China
Article ID: 3050
Keywords: UAV; prescribed performance control; adaptive sliding mode observer; disturbance estimation and compensation; nonlinear control strategy; finite-time convergence; aerial robotics

Abstract

The trajectory tracking accuracy of quadrotor UAVs is greatly challenged by external disturbances and model uncertainties. To overcome these issues, this paper presents a prescribed performance control approach incorporating a dynamic adaptive sliding mode observer. First, external disturbances and model uncertainties are treated as lumped disturbances within the quadrotor UAV system. By designing a sliding mode observer with a nonlinear gain adjustment mechanism, these disturbances can be estimated and compensated for in real time, without requiring prior knowledge of their bounds. Building upon this, the prescribed performance function is further improved, and a new performance function independent of initial conditions is developed to find out that the system states converge within the predefined performance boundaries, achieving precise trajectory tracking. The system’s convergence is rigorously analysed with Lyapunov stability theory. And we can make sure the method using lots of simulations. The results indicate algorithm achieves fast error convergence and precise trajectory tracking, even in the presence of dynamic environmental disturbances.

Published
2025-09-29
How to Cite
Xu, Q., & Zhang, L. (2025). Preconditioned Performance Trajectory Tracking Control of a Dynamic Adaptive Sliding Mode Observer for Quadrotor UAV. Advances in Differential Equations and Control Processes, 32(3). https://doi.org/10.59400/adecp3050
Section
Article
Supporting Agencies

This research was supported by the Doctoral Special Project of Jiangsu Province’s “Double Creation Program” (2408014/003) and the topic Design and Research on Perceptual User Selection Based on Scoring Region Subspace (223202).

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