A Single-Neuron-Based Temperature Control of a Continuous Stirred Tank Reactor

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dc.contributor.authorLadjouzi, Samir
dc.contributor.authorGrouni, Said
dc.date.accessioned2024-05-26T07:28:54Z
dc.date.available2024-05-26T07:28:54Z
dc.date.issued2024
dc.description.abstractIn this paper, a new technique to determine the best values of a PID controller is presented. The proposed scheme is based on using a single-neuron controller which its weights represent the PID parameters. Weight’s adjustment is accomplished with a recent meta-heuristic algorithm called the DragonFly Algorithm. To show the effectiveness of our method, we have applied it to control a Continuous Stirred Tank Reactor. The obtained results are compared with several algorithms: the Ziegler–Nichols, Genetic Algorithm, and Particle Swarm Optimization.en_US
dc.identifier.issn0970-3950
dc.identifier.urihttps://link.springer.com/article/10.1007/s12647-024-00749-y
dc.identifier.urihttps://doi.org/10.1007/s12647-024-00749-y
dc.identifier.urihttps://dspace.univ-boumerdes.dz/handle/123456789/13981
dc.language.isoenen_US
dc.publisherSpringer Natureen_US
dc.relation.ispartofseriesMapan - Journal of Metrology Society of India/ Vol. 39, N° 3(2024), PP. 707 - 719
dc.subjectContinuous stirred tank reactoren_US
dc.subjectDragonFly algorithmen_US
dc.subjectGenetic algorithm and particle swarm optimizationen_US
dc.subjectPID controlleren_US
dc.subjectSingle-neuron controlleren_US
dc.subjectZiegler–Nicholsen_US
dc.titleA Single-Neuron-Based Temperature Control of a Continuous Stirred Tank Reactoren_US
dc.typeArticleen_US

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