This paper presents a revised genetic algorithm (RGA) for parameter adjustment of nonlinear controllers. The RGA is based on the principle of selecting stabilizable chromosomes. The quadratic stabilization technique is used to realize the principle, i.e., to check stabilizability of the chromosomes which describes the parameters of nonlinear controller in the form of binary notation. In addition, the RGA has an index parameter of the robustness for control systems. It is, therefore, possible to design robust controllers by appropriately selecting a value of the index parameter. This simulation results show that the RGA can realize avoidance of instability phenomenon, fast parameter adjustment and robust controller design.