Modern turbojet engines are controlled using digital controllers. First of all, the micro turbojet engine discrete model is identified. System identification technique utilized real data obtained from jet cat P200sx engine running experiments. Digital PID controllers are mostly used for controlling these engines. The tuning techniques for digital PID controller parameters are of a great interest. Two tuning techniques are used in this paper to tune the PID controller parameters for the discrete model obtained. In the first, model based local optimal control technique is used to tune the PID controller parameters around certain operating points along the whole range. This technique is used for the first time with the concerned engine. The gain scheduling is used to manage the controller parameters around these operating points. In the second technique, genetic algorithms are used at different operating points along the whole range of operation. Also, the gain scheduling is used to manage the controller parameters around these operating points. The two tuning techniques are compared in Matlab simulation environment. The comparison is based on each controller robustness against noise effect and disturbance rejection. The simulated results are discussed and show better behavior for the digital PID controller tuned using model based local optimal control.