Hyper-redundant robots, robots with many degrees of freedom, are considered to be advantageous in many tasks, such as minimally invasive surgery, surveillance and inspection. However, due to their hyper degrees of freedom, the control of hyper-redundant robots is always challenging. Several fitting algorithms, which iteratively fit a hyper-redundant robot into a continuous curve, have been proposed to control the configuration of hyper-redundant robots. However, these algorithms require heavy computation, preventing them from being used in practice. In this study, we propose a novel modular control scheme for a hyper-redundant robot to reduce the computational load by dividing the robot into smaller modules and fitting each module separately. A Jacobian-based position control algorithm is also used to utilize the redundancy of each module to ensure that the overall configuration of the robot resembles the given desired curve. Simulation results show that the proposed scheme can be used to control hyper-redundant robots effectively.