Computational intelligence approach to PID controller design using the universal model |
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Authors: | Rodrigo Rodrigues Sumar |
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Affiliation: | a Federal University of Technology (UTFPR), Campus Cornélio Procópio, Alberto Carazzai, 1640, Zip code 86300-000, Cornéllio Procópio, PR, Brazil b Department of Automation and Systems, Federal University of Santa Catarina (UFSC), Zip code 88040-900, Florianópolis, SC, Brazil c Industrial and Systems Engineering Graduate Program (PPGEPS), Pontifical Catholic University of Paraná (PUCPR), Imaculada Conceição, 1155, Zip code 80215-901, Curitiba, Paraná, Brazil |
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Abstract: | Despite the popularity of PID (Proportional-Integral-Derivative) controllers, their tuning aspect continues to present challenges for researches and plant operators. Various control design methodologies have been proposed in the literature, such as auto-tuning, self-tuning, and pattern recognition. The main drawback of these methodologies in the industrial environment is the number of tuning parameters to be selected. In this paper, the design of a PID controller, based on the universal model of the plant, is derived, in which there is only one parameter to be tuned. This is an attractive feature from the viewpoint of plant operators. Fuzzy and neural approaches - bio-inspired methods in the field of computational intelligence - are used to design and assess the efficiency of the PID controller design based on differential evolution optimization in nonlinear plants. The numerical results presented herein indicate that the proposed bio-inspired design is effective for the nonlinear control of nonlinear plants. |
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Keywords: | PID control Nonlinear systems Fuzzy systems Neural networks Differential evolution Optimization |
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