Modeling and Control of an Experimental pH Neutralization Plant using Neural Networks based Approximate Predictive Control
نویسندگان
چکیده
A nonlinear experimental pH neutralization plant is controlled using a neural networks based Approximate Predictive Control (APC) strategy. First a closed-loop identification is performed, further, using neural networks, a black-box modeling of the experimental plant is conducted. Then the approximate predictive controller is realized, where a linear model of the plant is extracted at each sampling period from the neural network model. This strategy is used to control the experimental neutralization plant for set point tracking and disturbance rejection.
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