Abstarct: The aim of this project is to design a PID controller for the boost DC/DC converter that is tuned online using intelligent algorithms. The boost converter is notoriously difficult to robust control optimally using PID controller because it is a non-linear, variable structure, non-minimum phase plant and naturally has chaotic behavior.Specially if use the linear model of converter for design PID controller, it is possible that when we apply it to real model(physical sysytem) result in unstable performance of converter, for example in where we consider large signal of converter. Hence PID controller should be as tunning online strategy. Genetic Algorithms are effective at finding high performance areas in large domains and are the ideal choice to tune the online PID controller. By use of neural network an adaptive controller is designed such that in any changes in operation point , don’t require to redesign the PID controller. Also, by use of genetic algorithm improving the chaotic bihavior of converter. The simulation results show success the applying genetic algorithm and neural network in design PID controller for converter and they are outperformed standard tuning practices, e.g. Ziegler Nichols, at designing PID controller in face of a wide range of changes for the converter’s operating conditions. Also they are demonstrator that the Mean Square Error (MSE) performance criterion produces the most effective PID controllers when compared with other performance criterion.