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

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Abstract

In 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.

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Authors and Affiliations

  1. Department of Electrical Engineering, Faculty of Sciences and Applied Sciences, University of Bouira, Rue Frères Boussendalah, 10000, Bouira, Algeria

    Samir Ladjouzi

  2. Industrial Maintenance Department, Faculty of Sciences Engineering, University UMBB of Boumerdes, Av. de L’Indépendance, 35000, Boumerdes, Algeria

    Said Grouni

Authors
  1. Samir Ladjouzi
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  2. Said Grouni
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Correspondence to Samir Ladjouzi.

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Ladjouzi, S., Grouni, S. A Single-Neuron-Based Temperature Control of a Continuous Stirred Tank Reactor. MAPAN (2024). https://doi.org/10.1007/s12647-024-00749-y

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