Abstract : Over the past years, it has been clearly noticed that the power demand has undergone a rapid growth worldwide due to increase in the rate of population, industrial growth and consequently the need of electric power. As a result, power grids have undergone to a significant evolution in generation, transmission and distribution systems and has become more complex and challenging. A better utilization of the existing electricity transmission networks to the maximum extent will be more effective and economical as long as the system security, stability, and reliability are not compromised. So, an innovative solution was proposed to obtain better utilization and controlling of power over the transmission network in steady state and transient conditions is by using the Flexible AC Transmission System (FACTS) devices which are considered as power electronics technology. In this research, Unified Power Flow Controller is being studied as it is considered the most powerful and versatile model of FACTS devices family. Moreover, the controllers which are being used in UPFC are very important to control the transmission lines parameters as desired. One of the conventional controllers which are being used today is the conventional PI controllers. In this study, the conventional PI controllers will be replaced by a Model Predictive Controller and Controllers based on an Artificial Neural Networks such as Neural Network Predictive Controller and Nonlinear autoregressive moving average controller. This is in order to investigate the robustness, effectiveness and the capability of such controllers to accommodate any sudden change in the transmission lines parameters such as the voltage magnitude, impedance and the phase angle.