article · PLoS ONE
Quadcopter unmanned aerial vehicles require precise control systems to track planned flight paths when facing external disturbances. A control method combining a super twisting sliding mode controller with a novel fuzzy proportional-integral-derivative surface addresses this need. Developed using a six-degrees-of-freedom dynamic model, the system uses fuzzy logic to automatically tune its gain parameters, enhancing overall robustness while reducing undesirable control chattering. Lyapunov stability analysis confirms the theoretical safety and reliability of the approach. When tested across diverse trajectories, parameter fluctuations, and disturbance conditions in numerical simulations, the design demonstrates superior tracking accuracy, disturbance rejection, and resilience compared to existing sliding mode variants. Furthermore, the controller produces minimal, smooth control actions, pointing to operational safety and lower energy demands for aerial platforms during complex flight missions.
Unmanned aerial vehicles must fly reliably despite turbulent weather and changing operational conditions. By reducing flight path errors and eliminating harsh, jerky control responses, advanced control algorithms make aerial navigation more dependable. Smoother control outputs also prevent excessive mechanical stress and battery drain, helping quadcopters operate safely and efficiently during critical operations.
This research could enable more resilient flight automation for quadrotor manufacturers and drone software developers handling delivery, surveillance, or inspection tasks in turbulent environments. At present, the technology is at an early simulation stage, having been evaluated entirely through numerical modelling rather than physical flight hardware. Moving towards practical use will require physical prototyping and validation on commercial drone platforms under actual outdoor weather conditions.
AI-generated from the published abstract. Always read the original work before citing.
This paper presents Super Twisting Sliding Mode Control with a novel Fuzzy PID Surface for improved trajectory tracking of quadrotor unmanned aerial vehicles under external disturbances. First, quadrotor dynamic model with six degrees of freedom (6-DOF) is developed using Newton-Euler Method. Then, a robust Sliding Mode Control based on a new Fuzzy PID Surface is designed to be capable of automatically adjusting its gain parameters. The proposed SMC controller applies super twisting algorithm with PID surface to reduce chattering and a fuzzy logic controller to automatically adjust the gain parameters in order to enhance robustness. Furthermore, the solution to stability has been given by the Lyapunov method. The controller's performance is tested through various trajectories, parameter variations, and disturbance scenarios, comparing it with recent alternatives such as Sliding Mode Control, Fuzzy Sliding Mode Control, and Fuzzy Super Twisting Sliding Mode Control using numerical simulations. The simulation results show that the proposed controller has better tracking performance, parameter variation handling, and disturbance rejection capability compared with the aforementioned controllers. Additionally, the control efforts of the proposed method are minimal and smooth, proving it to be an economically feasible controller and operationally safe for the quadrotor.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.1371/journal.pone.0308997
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
