This article presents a real-time control system for an agricultural mobile machine (vehicle) based on an on-board vision system using a single camera. This system has been designed in order to help human beings in repetitive and di cult tasks in the agricultural domain. The aim of the robotics application concerns the control of the vehicle with regard to the reap limit detected in image space. The perception aspect in relation with the application has been described in previous work, and here we deal with the control aspect. We integrate image features issued from the modelling of the scene in the control loop, in order to perform image-based servoing technique. The vehicle behaviour described here concerns bicycle and neural models, and three control laws are then synthesized. The rst and the second are modelling approaches and use an interaction between the scene and the image space. They are based on regulation of a task function. The third is a \black-box modelling" technique and is based on a neural network. Finally, experimental results obtained with these di erent control laws in different conditions are presented and discussed.