Optimization of Multivariable System Control Using Neural Network-Based Control
This paper shows the improvement of controller designing for a multivariable system, through the implementing
and testing in real-time the classical methods for controlling the nonlinear multi-input multi-output system (MIMO), where
the decentralized strategy, the proportional-integral-derivative controller (PID) used and the advanced method where the
dynamic decoupling approach implemented and tested in real-time and the proposed strategy by using intelligent controller
where the neural network-based internal model controller (DIC) and internal model controller (IMC) are concisely described
and tested in real-time. A short study of the advantages and disadvantages of the proposed strategy compared with the
classical strategies. The whole software algorithms were designed and tested in real-time by NI LabVIEW software.
Keywords - Multivariable System, Decentralized Strategy, Dynamic Decoupling, Neural Network, LabVIEW.