Abstract
The neural networks can be applied to the model based controllers such as the model predictive control (MPC) and the internal model control (IMC). On the other hand, one can construct adaptive controllers by using the inverse dynamic models which are updated on-line. The special inverse learning (SIL) or the error feedback learning (EFL) can be applicable for this. These control strategies are compared with each other through the numerical simulation of SISO and MIMO control problems of the continuous polymerization reactor.
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