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Intelligent Observer-Based Feedback Linearization for Autonomous Quadrotor Control

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dc.contributor.authorNoor Hanis Izzuddin Mat Lazimen_US
dc.contributor.authorAbdul Rashid Husainen_US
dc.contributor.authorNurul Adilla Mohd Subhaen_US
dc.contributor.authorMohd Ariffanan Mohd Basrien_US
dc.date.accessioned2024-05-28T03:34:17Z
dc.date.available2024-05-28T03:34:17Z
dc.date.issued2018
dc.description.abstractThe presence of disturbances can cause instability to the quadrotor flight and can be dangerous especially when operating near obstacles or other aerial vehicles. In this paper, a hybrid controller called state feedback with intelligent disturbance observer-based control (SF-iDOBC) is developed for trajectory tracking of quadrotor in the presence of time-varying disturbances, e.g. wind. This is achieved by integrating artificial intelligence (AI) technique with disturbance observer-based feedback linearization to achieve a better disturbance rejection capability. Here, the observer estimates the disturbances acting on the quadrotor, while AI technique using the radial basis func-tion neural network (RBFNN) compensates the disturbance estimation error. To improve the error compensation of RBFNN, the k-means clustering method is used to find the optimal centers of the Gaussian activation function. In addition, the weights of the RBFNN are tuned online using the derived adaptation law based on the Lyapunov method, which eliminates the offline training. In the simulation experiment conducted, a total of four input nodes and five hidden neurons are used to compensate for the error. The results obtained demonstrate the effectiveness and merits of the theoretical development.en_US
dc.identifier.citationM. LAZIM, Izzuddin et al. Intelligent Observer-Based Feedback Linearization for Autonomous Quadrotor Control. International Journal of Engineering & Technology, [S.l.], v. 7, n. 4.35, p. 904-911, nov. 2018. ISSN 2227-524X. Available at: <https://www.sciencepubco.com/index.php/ijet/article/view/26280>. Date accessed: 26 feb. 2022. doi:http://dx.doi.org/10.14419/ijet.v7i4.35.26280.en_US
dc.identifier.doi10.14419/ijet.v7i4.35.26280
dc.identifier.epage911
dc.identifier.issn2227-524X
dc.identifier.issue4.35
dc.identifier.other2394-3
dc.identifier.spage904
dc.identifier.urihttps://www.sciencepubco.com/index.php/ijet/article/view/26280
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/4707
dc.identifier.volume7
dc.language.isoenen_US
dc.publisherScience Publishing Corporation Incen_US
dc.relation.ispartofInternational Journal of Engineering & Technology (UAE)en_US
dc.subjectDisturbance Observer; Feedback Linearization; K-means clustering; Neural Network; Quadcopteren_US
dc.titleIntelligent Observer-Based Feedback Linearization for Autonomous Quadrotor Controlen_US
dc.typeArticleen_US
dspace.entity.typePublication

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