Adaptive Modified RISE Control for Quadrotors: Enhancing Trajectory Tracking Through Uncertainty Compensation

Autonomous quadrotors are increasingly deployed in environments with significant uncertainties and disturbances, where ensuring robust trajectory tracking is critical for safety and performance. This paper presents an adaptive modified robust inverse of signum error (AM-RISE) control method, which achieves reliable trajectory tracking control for a quadrotor autonomous aerial vehicle (AAV). The proposed method systematically accounts for gyroscopic effects, rotor dynamics, parametric uncertainties, and external disturbances, ensuring robust performance across varying trajectory speeds. Through novel mathematical manipulation in the error system development, the quadrotor dynamics are expressed in a control-oriented form, which explicitly incorporates the uncertainty in the gyroscopic term and control actuation term. An adaptive modified RISE law is then designed to stabilize both the position and attitude loops of the quadrotor system. A rigorous Lyapunov-based analysis is utilized to prove asymptotic trajectory tracking, where the region of convergence can be made arbitrarily large through judicious control gain selection. Moreover, the stability analysis formally addresses gyroscopic effects and actuator uncertainty. To illustrate the performance of the control law, comparative numerical simulation results are provided, which demonstrate the improved closed-loop performance achieved under varying levels of parametric uncertainty, disturbance magnitudes and trajectory speeds.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3612215
Primary Topic
Vehicle Dynamics and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Adaptive Modified RISE Control for Quadrotors: Enhancing Trajectory Tracking Through Uncertainty Compensation

Musabbir Ahmed Arrafi, Krishna Bhavithavya Kidambi, Kevin Johnston, Madhur Tiwari
IEEE Access
Vehicle Dynamics and Control Systems
article

Adaptive Modified RISE Control for Quadrotors: Enhancing Trajectory Tracking Through Uncertainty Compensation

Musabbir Ahmed Arrafi, Krishna Bhavithavya Kidambi, Kevin Johnston, Madhur Tiwari
article en

Abstract

Autonomous quadrotors are increasingly deployed in environments with significant uncertainties and disturbances, where ensuring robust trajectory tracking is critical for safety and performance. This paper presents an adaptive modified robust inverse of signum error (AM-RISE) control method, which achieves reliable trajectory tracking control for a quadrotor autonomous aerial vehicle (AAV). The proposed method systematically accounts for gyroscopic effects, rotor dynamics, parametric uncertainties, and external disturbances, ensuring robust performance across varying trajectory speeds. Through novel mathematical manipulation in the error system development, the quadrotor dynamics are expressed in a control-oriented form, which explicitly incorporates the uncertainty in the gyroscopic term and control actuation term. An adaptive modified RISE law is then designed to stabilize both the position and attitude loops of the quadrotor system. A rigorous Lyapunov-based analysis is utilized to prove asymptotic trajectory tracking, where the region of convergence can be made arbitrarily large through judicious control gain selection. Moreover, the stability analysis formally addresses gyroscopic effects and actuator uncertainty. To illustrate the performance of the control law, comparative numerical simulation results are provided, which demonstrate the improved closed-loop performance achieved under varying levels of parametric uncertainty, disturbance magnitudes and trajectory speeds.

IEEE Access
Florida Institute of Technology (US), University of Dayton (US)
Openalex Percentile: Top 72%
Vehicle Dynamics and Control Systems
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Adaptive Modified RISE Control for Quadrotors: Enhancing Trajectory Tracking Through Uncertainty Compensation — Musabbir Ahmed Arrafi, Krishna Bhavithavya Kidambi, et al. · IEEE Access (2025) | TGRS Research Map | TGRS