{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T14:26:07Z","timestamp":1766067967443,"version":"3.41.2"},"reference-count":28,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,5,30]],"date-time":"2024-05-30T00:00:00Z","timestamp":1717027200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurorobot."],"abstract":"<jats:p>Unmanned Aerial Vehicles (UAVs) and quadrotors are being used in an increasing number of applications. The detection and management of forest fires is continually improved by the incorporation of new economical technologies in order to prevent ecological degradation and disasters. Using an inner-outer loop design, this paper discusses an attitude and altitude controller for a quadrotor. As a highly nonlinear system, quadrotor dynamics can be simplified by assuming several assumptions. Quadrotor autopilot is developed using nonlinear feedback linearization technique, LQR, SMC, PD, and PID controllers. Often, these approaches are used to improve control and to reject disturbances. PD-PID controllers are also deployed in the tracking and surveillance of smoke or fire by intelligent algorithms. In this paper, the efficiency using a combined PD-PID controllers with adjustable parameters have been studied. The performance was assessed by simulation using matlab Simulink. The computational study conducted to assess the proposed approach showed that the PD-PID combination presented in this paper yields promising outcomes.<\/jats:p>","DOI":"10.3389\/fnbot.2024.1363366","type":"journal-article","created":{"date-parts":[[2024,5,30]],"date-time":"2024-05-30T12:14:59Z","timestamp":1717071299000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["On designing a configurable UAV autopilot for unmanned quadrotors"],"prefix":"10.3389","volume":"18","author":[{"given":"Ali","family":"Bhar","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mounir","family":"Sayadi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2024,5,30]]},"reference":[{"volume-title":"Planification de trajectoires pour une flotte d'UAVs","year":"2010","author":"Ait El Cadi","key":"ref1"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"15","DOI":"10.3390\/drones5010015","article-title":"Unmanned aerial vehicles for wildland fires: sensing, perception, cooperation and assistance","volume":"5","author":"Akhloufi","year":"2021","journal-title":"Drones"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"1812","DOI":"10.1049\/iet-cta.2011.0348","article-title":"Model predictive quadrotor control: attitude, altitude and position experimental studies","volume":"6","author":"Alexis","year":"2012","journal-title":"IET Control Theory Appl."},{"key":"ref5","doi-asserted-by":"publisher","first-page":"4764","DOI":"10.3390\/app12094764","article-title":"Deep reinforcement learning-based adaptive controller for trajectory tracking and altitude control of an aerial robot","volume":"12","author":"Barzegar","year":"2022","journal-title":"Appl. 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