Application of Advanced Control in Quadrotor UAVs

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Abstract This work focused on the control of a quadrotor Unmanned Aerial Vehicle (UAV) by first deriving its dynamic model using the Newton-Euler method and validating it with the Lagrange-Euler formulation for accuracy. A simulation function based on these equations was developed and tested in open-loop conditions with predefined control inputs to understand the system's dynamic behavior. Four control strategies were implemented and evaluated to regulate altitude, attitude, heading, and position: classical PID and PD controllers, a Linear Quadratic Regulator (LQR), and advanced nonlinear approaches including Backstepping Control and Sliding Mode Control (SMC). The controllers were implemented in MATLAB and rigorously tested through simulations to assess performance and stability. The comparative analysis showed that all controllers had similar rise time, settling time, and overshoot but exhibited unique traits. The PD controller was simple and fast but showed overshoot and minor steady-state error. Backstepping Control had good performance but required careful tuning due to parameter sensitivity. SMC achieved the lowest overshoot but had slower response and induced chattering that may harm actuators. LQR yielded the fastest response but with significant overshoot. This study highlights the importance of selecting control techniques matched to specific performance criteria. While classical methods are straightforward, advanced nonlinear and robust controls provide better precision and reliability for quadrotor UAVs under diverse conditions.
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Application of Advanced Control in Quadrotor UAVs | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Application of Advanced Control in Quadrotor UAVs Yasmine Zamoum, Razika Boushaki, Maria Laifaoui, Fadhila Kahoul This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9618715/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract This work focused on the control of a quadrotor Unmanned Aerial Vehicle (UAV) by first deriving its dynamic model using the Newton-Euler method and validating it with the Lagrange-Euler formulation for accuracy. A simulation function based on these equations was developed and tested in open-loop conditions with predefined control inputs to understand the system's dynamic behavior. Four control strategies were implemented and evaluated to regulate altitude, attitude, heading, and position: classical PID and PD controllers, a Linear Quadratic Regulator (LQR), and advanced nonlinear approaches including Backstepping Control and Sliding Mode Control (SMC). The controllers were implemented in MATLAB and rigorously tested through simulations to assess performance and stability. The comparative analysis showed that all controllers had similar rise time, settling time, and overshoot but exhibited unique traits. The PD controller was simple and fast but showed overshoot and minor steady-state error. Backstepping Control had good performance but required careful tuning due to parameter sensitivity. SMC achieved the lowest overshoot but had slower response and induced chattering that may harm actuators. LQR yielded the fastest response but with significant overshoot. This study highlights the importance of selecting control techniques matched to specific performance criteria. While classical methods are straightforward, advanced nonlinear and robust controls provide better precision and reliability for quadrotor UAVs under diverse conditions. UAV PID Controller PD Controller SMC LQR Backstepping Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 15 May, 2026 Reviewers invited by journal 06 May, 2026 Editor assigned by journal 06 May, 2026 Submission checks completed at journal 06 May, 2026 First submitted to journal 05 May, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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