Adaptive Reconfigurable Learning Algorithm for Robust Optimal Longitudinal Motion Control of Unmanned Aerial Vehicles

This study presents the formulation and verification of a novel online adaptive reconfigurable learning control algorithm (RLCA) for improved longitudinal motion control and disturbance compensation in Unmanned Aerial Vehicles (UAVs). The proposed algorithm is formulated to track the optimal traject...

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Bibliographic Details

Published in:	Algorithms
Main Authors:	Omer Saleem, Aliha Tanveer, Jamshed Iqbal
Format:	Article
Language:	English
Published:	MDPI AG 2025-03-01
Subjects:	unmanned aerial vehicle adaptive control reconfigurable learning algorithm longitudinal motion disturbance rejection
Online Access:	https://www.mdpi.com/1999-4893/18/4/180