Neural Network Toolbox

System Identification

The first stage of model predictive control is to train a neural network to represent the forward dynamics of the plant. The prediction error between the plant output and the neural network output is used as the neural network training signal. The process is represented by the following figure.

The neural network plant model uses previous inputs and previous plant outputs to predict future values of the plant output. The structure of the neural network plant model is given in the following figure.

This network can be trained offline in batch mode, using data collected from the operation of the plant. Any of the training algorithms discussed in Backpropagation, can be used for network training. This process is discussed in more detail later in this chapter.

NN Predictive Control

Predictive Control

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