In this paper, we studied the feedback stabilization of an inductive power transfer system based on available output measurement. The proposed controller relies on a full-order state observer in order to estimate the unmeasured state. The control design problem is challenging due to the large dimension of the closed-loop system, which requires too many tuning parameters to be determined when conventional control methods are employed. To solve this issue, we propose an LQR methodology based on a genetic algorithm such that the weighing coefficients of the cost function matrices can be automatically computed in an optimized manner. The proposed approach combines the method of eigenstructure assignment and the LQR technique in order to design both the controller and the observer gain matrices. The design methodology provides a systematic way to compute the parameters of the LQR technique for a wireless power transfer system in an optimized manner, which can be a useful design tool for many other applications. The effectiveness of the approach was verified by numerical simulation on the dynamic model of the wireless power transfer system. The results show that the proposed design outperforms conventional design methods in terms of a better performance and reduced design iterations effort.