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dc.contributor.authorLeal, Isaac S.; orcid: 0000-0002-3351-0491; email: isaac.sanchezleal@miun.se
dc.contributor.authorAbeykoon, Chamil; orcid: 0000-0002-6797-776X; email: chamil.abeykoon@manchester.ac.uk
dc.contributor.authorPerera, Yasith S.; orcid: 0000-0002-1988-2766; email: yasiths@uom.lk
dc.date.accessioned2021-09-14T01:06:29Z
dc.date.available2021-09-14T01:06:29Z
dc.date.issued2021-09-10
dc.identifierhttps://chesterrep.openrepository.com/bitstream/handle/10034/625851/additional-files.zip?sequence=2
dc.identifierhttps://chesterrep.openrepository.com/bitstream/handle/10034/625851/electronics-10-02218-v2.pdf?sequence=3
dc.identifierhttps://chesterrep.openrepository.com/bitstream/handle/10034/625851/electronics-10-02218.xml?sequence=4
dc.identifier.citationElectronics, volume 10, issue 18, page e2218
dc.identifier.urihttp://hdl.handle.net/10034/625851
dc.descriptionFrom MDPI via Jisc Publications Router
dc.descriptionHistory: accepted 2021-09-07, pub-electronic 2021-09-10
dc.descriptionPublication status: Published
dc.description.abstractUnmanned aerial vehicles or drones are becoming one of the key machines/tools of the modern world, particularly in military applications. Numerous research works are underway to explore the possibility of using these machines in other applications such as parcel delivery, construction work, hurricane hunting, 3D mapping, protecting wildlife, agricultural activities, search and rescue, etc. Since these machines are unmanned vehicles, their functionality is completely dependent upon the performance of their control system. This paper presents a comprehensive approach for dynamic modeling, control system design, simulation and optimization of a quadcopter. The main objective is to study the behavior of different controllers when the model is working under linear and/or non-linear conditions, and therefore, to define the possible limitations of the controllers. Five different control systems are proposed to improve the control performance, mainly the stability of the system. Additionally, a path simulator was also developed with the intention of describing the vehicle’s movements and hence to detect faults intuitively. The proposed PID and Fuzzy-PD control systems showed promising responses to the tests carried out. The results indicated the limits of the PID controller over non-linear conditions and the effectiveness of the controllers was enhanced by the implementation of a genetic algorithm to autotune the controllers in order to adapt to changing conditions.
dc.languageen
dc.publisherMDPI
dc.rightsLicence for this article: https://creativecommons.org/licenses/by/4.0/
dc.sourceeissn: 2079-9292
dc.subjectquadcopter
dc.subjectunnamed aerial vehicle
dc.subjectdynamic model
dc.subjectPID controller
dc.subjectfuzzy logic
dc.subjectgenetic algorithm
dc.subjectintelligent control
dc.titleDesign, Simulation, Analysis and Optimization of PID and Fuzzy Based Control Systems for a Quadcopter
dc.typearticle
dc.date.updated2021-09-14T01:06:28Z
dc.date.accepted2021-09-07


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