Designing controllers for modular robots is difficult due to the distributed and dynamic nature of the robots. In this paper fractal gene regulatory networks are evolved to control modular robots in a distributed way. Experiments with different morphologies of modular robot are performed and the results show good performance compared to previous results achieved using learning methods. Furthermore, some experiments are performed to investigate evolvability of the achieved solutions in the case of module failure and it is shown that the system is capable of come up with new effective solutions.