Paper Title
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.