In order to improve the control performance of the electrohydraulic servo system for the adjustable nozzle of a ramjet engine, the load flow rate and the load pressure were defined, and the linear system model was established with the small deviation method, and a controller based on the adaptive improved genetic algorithm was designed. Three parameters of proportional, integral and differential in the classic PID control and fiftyeight parameters of membership functions and control rules in the intelligent fuzzy control were optimized globally. The former used binary coding, and the latter adopted decimal coding. The optimization overcame that the process greatly depended on the designer’s experience and the controller didn’〖KG-*3〗t reach the best performance. MATLAB was used to simulate the digital discrete system. The results show that the optimized PID control of genetic algorithm can reduce the adjustment time and overshoot, and the optimized fuzzy control can shorten the response time and has no overshoot. The latter response time and overshoot are less than the former, namely the nonlinear intelligent fuzzy control has more optimization potential than linear PID control.