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Cited by 4Adaptive Control of Nonlinear SystemsStability and Control of Uncertain SystemsAerospace Engineering and Control Systems

The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index; none of the 9 sources its claims cite is checked for support yet.

Predefined time trajectory tracking control and hardware in loop verification for quadrotor UAV under input delay and disturbances

Open access
Li, Shuo, Duan, Na, Pei, Hailong·2025·Asian Journal of Control

Abstract

This paper deals with the predefined time trajectory tracking control of quadrotor unmanned aerial vehicle (UAV) system in the presence of input delay and external disturbances. By combining the backstepping with the predefined time nonlinear disturbance observer, the uncertainty caused by the external disturbance is eliminated, enabling the UAV to reach the control target within a predefined time. Moreover, in order to compensate for the impact of the control input delay, an appropriate auxiliary system is introduced. Simulation and hardware‐in‐the‐loop (HIL) experimental are carried out to show the effectiveness of the proposed control scheme.

Overview

CoChat Summary

Written by AI from the paper’s full text.

TL;DR

This paper proposes a predefined-time trajectory tracking control scheme for a quadrotor UAV subject to input delay and external disturbances, combining backstepping, predefined-time nonlinear disturbance observers, and auxiliary systems for delay compensation. Simulations and Pixhawk hardware-in-the-loop experiments indicate tracking and disturbance estimation within the predefined times.

Key findings

  • Predefined-time nonlinear disturbance observers estimate external disturbances in each loop; simulation results show observer estimation errors converge around 0.6 s.
  • In simulation, the UAV tracks the desired flight trajectory and attitude in about 0.7√2 s, with position and attitude tracking errors converging within 0.7√2 s.
  • The auxiliary system compensates input delay; as input delay increases, tracking speed slows and tracking error increases.
  • Compared with ordinary NDO and ESO, the proposed predefined NDO lets the z channel track z_d = 3.5 m more quickly within the predefined time with smaller tracking-error fluctuation. In HIL tests, the UAV flies smoothly and maintains target pitch, roll, and yaw angles of 0.26°, 0.35°, and 176.66°, respectively.

Methods

  • Design: backstepping position and attitude controllers with predefined-time nonlinear disturbance observers and auxiliary dynamical systems for input delay; Lyapunov-based stability proofs are given in Theorems 1–4.
  • Data/sample: numerical simulation of an F450 quadrotor with m = 2.5 kg, I_x = I_y = 0.082 kg·m², I_z = 0.149 kg·m², l = 0.325 m, τ = 0.01, initial position (0.3, 0.3, 0.3) m, initial Euler angles (0, 0, 0.3) rad, desired position (2, 4, 3.5) m, desired yaw 0 rad, and disturbances such as d₁ = 5 sin 2t.
  • Analysis: Lyapunov stability arguments for predefined-time convergence, plus numerical simulations and hardware-in-the-loop experiments using the RflySim platform and Pixhawk flight control.

Limitations

  • Stated: future work will focus on predefined-time flight tracking control to overcome state constraints and actuator failures, implying these are not addressed in the present work.
  • Stated assumptions: the geometric center coincides with the center of gravity; the UAV is a rigid body with uniform symmetry; mass and moment of inertia are constant; disturbances are differentiable with bounded derivatives; and the input delay is known and non-negative.
  • Evident from the text: validation is limited to numerical simulation and hardware-in-the-loop experiments, not real outdoor flight, and robustness to unknown delay or actuator faults is not demonstrated.

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Integrity signals

Registry

Crossref · 10.1002/asjc.3557

Cites

39 of 39 references verified0 citation errors · 0 not checkable

Statistics

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Verification

Claims the paper makes

22 Own result · 9 Sources not found · 6 Own interpretation · 3 No basis given

  • It may state two separate claims as one. 21
  • Probably not a substantial claim. 3

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Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

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Citations

Cites

Research works printed but not linked: 3

  1. Liu H. T., 2023, Event‐triggered predefined‐time H∞$$ {H}_{\infty } $$ formation control for multiple underactuated surface vessels with error constraints and input quantization, Ocean Eng., 114294, 277
  2. 10.1002/asjc.344420 · DOI
  3. Zhang Z. S., 2021, Fuzzy sampled‐data H∞$$ {H}_{\infty } $$ sliding‐mode control for active hysteretic suspension of commercial vehicles with unknown actuator‐disturbance, Ocean Eng., 117, 104940

Cited by

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Metadata

Authors
Li, S., Duan, N., & Pei, H.
Affiliations
  • Key Laboratory of Autonomous Systems and Network Control, Ministry of Education (CN)
  • Jiangsu Normal University (CN)
Corresponding author
Pei, Hailong
Venue
Asian Journal of Control
Publisher
Wiley
Published
2025-01-14
Volume
27
Issue
4
Pages
1950-1963
ISSN
  • 1561-8625 (ISSN-L)
  • 1934-6093
OpenAlex
W4406376734
Cited by
4
References
39
Citations by year
2026: 4
FWCI
1.07
Type
journal article
Language
en
Open access
Locations
Asian Journal of Control (publishedVersion)
Funders
  • Aeronautical Science Foundation of China (20220056060001)
  • National Key Research and Development Program of China (2023YFB4704900)
  • Fundamental Research Funds for the Central Universities
Topics
  • Physical Sciences › Engineering › Control and Systems Engineering › Adaptive Control of Nonlinear Systems
  • Physical Sciences › Engineering › Control and Systems Engineering › Stability and Control of Uncertain Systems
  • Physical Sciences › Engineering › Aerospace Engineering › Aerospace Engineering and Control Systems
Keywords
quadrotor, predefined-time control, trajectory tracking, input delay, external disturbances, backstepping control, nonlinear disturbance observer, auxiliary systems, hardware-in-the-loop testing

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