Adaptive Nonlinear Proportional–Integral–Derivative Control of a Continuous Stirred Tank Reactor Process Using a Radial Basis Function Neural Network

Adaptive Nonlinear Proportional–Integral–Derivative Control of a Continuous Stirred Tank Reactor Process Using a Radial Basis Function Neural Network

Temperature control in a continuous stirred tank reactor (CSTR) poses significant challenges due to the process’s inherent nonlinearities and uncertain parameters. This study proposes an innovative solution by developing an adaptive nonlinear proportional–integral–derivative (NPID) controller. The n...

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Bibliographic Details
Main Authors: Joo-Yeon Lee, Gang-Gyoo Jin, Gun-Baek So
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Algorithms
Subjects:
CSTR
adaptive control
nonlinear PID controller
RBFNN
system identification
Online Access:https://www.mdpi.com/1999-4893/18/7/442
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