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Calculation of PID controller parameters by using a fuzzy neural network.

Ching-Hung Lee·Ching-Cheng Teng
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Abstract

In this paper, we use the fuzzy neural network (FNN) to develop a formula for designing the proportional-integral-derivative (PID) controller. This PID controller satisfies the criteria of minimum integrated absolute error (IAE) and maximum of sensitivity (Ms). The FNN system is used to identify the relationship between plant model and controller parameters based on IAE and Ms. To derive the tuning rule, the dominant pole assignment method is applied to simplify our optimization processes. Therefore, the FNN system is used to automatically tune the PID controller for different system parameters so that neither theoretical methods nor numerical methods need be used. Moreover, the FNN-based formula can modify the controller to meet our specification when the system model changes. A simulation result for applying to the motor position control problem is given to demonstrate the effectiveness of our approach.

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AlgorithmsComputer SimulationEquipment DesignFeedbackFuzzy LogicModels, TheoreticalNeural Networks, ComputerSensitivity and SpecificityEvaluation StudyJournal ArticleResearch Support, Non-U.S. Gov't

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Ching-Hung Lee, Ching-Cheng Teng. 2003. Calculation of PID controller parameters by using a fuzzy neural network.. https://doi.org/10.1016/s0019-0578(07)60142-6

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