One important factor to produce a qualified electricity is the stability of the system. An unstable system resulted an undamped oscilation of system, and the stable system can damp the oscilation quickly. Therefore, it is necessary to apply a stability device to a power system and it is called a Power System Stabilizer (PSS). One of stability design is a feedback control design. Here, in this research, the state feedback control are designed for Single Machine Infinite Bus (SMIB) . The SMIB model is non linear therefore the feedback control can’t be designed directly. Some researchers do linearize the system before design the feedback control. In this research, a nonlinear model of SMIB is build in a state space form. Subsequently, a fuzzification Takagi-Sugeno is applied. The state feedback controls are applied to design the control of SMIB fuzzy system, a state feedback gain is determined using method Routh Hurwitz. The determining the parameter of state feedback gain influence the performance of SMIB. Therefore, it is important to determine the suitable parameter such that the SMIB has the optimal performance. The Particle Swarm Optimization (PSO) is applied to optimaze the performance of SMIB. In these research, it is compared the performance of SMIB by applying between Routh Hurwitz, fuzzy Routh Hurwitz, PSO fuzzy Routh Hurwitz for state feedback control. The simulation result show that Performance of SMIB using The PSO Fuzzy Routh Hurwitz state feedback can improve the performance of SMIB, but the performance of Efd become oscillate and this method influence by the chosen parameter.
Stability Enhancement by Comparative Analysis of AI Techniques in Power System Stablizer Integrated With Hybrid System