The Power systems are subjected to low-frequency disturbances that might cause loss of synchronism and an eventual breakdown of the entire systems. The “low-frequency oscillations” is one of the operational constraints which limit bulk power transmission through the power networks, and also cause an eventual breakdown of the entire systems. For this problem power system stabilizers (PSSs) are used to generate supplementary control signals for the excitation system to damp the low-frequency power system oscillations and to offer an extra damping for the synchronous generators. The supplementary power system stabilizer must be capable of providing appropriate stabilization signals over a wide range of operating conditions, and disturbances. However, a conventional power system stabilizer (CPSS) provides a positive damping torque in phase with the speed signal to cancel the effect of the system negative damping torque, because of the gains of this controller are determined for a particular operating conditions. The conventional Power System Stabilizer which uses lead-lag compensation, where the gain settings designed for specific operating conditions, is providing poor performance under different loading conditions. The constantly changing nature of power system makes the design of CPSS a difficult task. Therefore, it is so difficult to design a stabilizer that could present a good performance in all operating points of electric power systems. This thesis is devoted to overcoming the drawback of conventional power system stabilizers (CPSSs), by designing and modeling of Adaptive Neuro-Fuzzy power system stabilizers (ANFPSSs). The new design has a capacity to suppress and damp the oscillations when the generators are subjected to different disturbances. The thesis deals with the design procedure for a fuzzy logic based PSS (FLPSS) and a self-learning adaptive neural network based power system stabilizer (ANFPSS) that improves the dynamic stability and provides supplementary signals as consequences of which extending the power stability limits. The speed deviation of a synchronous machine and acceleration are chosen as the input signals to the proposed controller. The proposed technique has the features of a simple structure, fast response, effective and the economical approach for attaining stabilization of the power systems. The damping time provided by ANFIS controller based power system stabilizer is 73% less in comparison to CPSS under three - Phase fault conditions.