NON-LINEAR CONTROL USING PARAMETER ESTIMATION FROM FORWARD NEURAL MODEL
A neural network application for system identification and control of
non-linear process is described in this paper. The non-linear identification is
mostly using feed-forward neural networks as a useful mathematical tool to build
a non-parametric model between the input and output of a real non-linear process.
The possibility of on-line estimation of the actual parameters from an off-line
trained neural model of the non-linear process using the gain matrix is considered
in this paper. This linearization technique is used in the algorithm of on-line
tuning of the controller parameters based on a pole placement control design for
the non-linear SISO process.
Keywords: neural model, NARMAX structure, non-linear parameter estimation