The precision agriculture and soil tillage are tasks which can be achieved by Automated Tractors (AT) through the integration of several servomechanisms. In order to reach a high autonomy under various work conditions of the AT, control laws’ design and tuning are paramount. The aim of this work is to develop an angle position controller for steering systems applied to an AT. We introduce an automatic electronic steering system by using a fuzzy model, obtained through an Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm training. A proportional derivative (PD) controller is also tuned through a Takagi-Sugeno fuzzy model (T-S). Furthermore, several closed-loop stability tests were carried out, in numerical simulation and real-time implementation. The feasibility of our methodology is illustrated through the tracking of several angles’ profiles in a real test scenario. For the tracking of a trajectory or several set-points, we have obtained mean errors about 0.6545 and 0.8651 degrees, respectively. Some mechatronic integrations to convert a conventional tractor into a basic Autonomous Agriculture Off-road Tractor (AAOT) are also shown.

精准农业和土壤耕作是自动拖拉机 (AT) 通过集成多个伺服机构可以实现的任务。为了在 AT 的各种工作条件下达到高度自治，控制律的设计和调整至关重要。这项工作的目的是为应用于 AT 的转向系统开发一种角度位置控制器。我们使用通过自适应神经模糊推理系统 (ANFIS) 算法训练获得的模糊模型来介绍自动电子转向系统。比例微分 (PD) 控制器也通过 Takagi-Sugeno 模糊模型 (TS) 进行调整。此外，在数值模拟和实时实施中进行了几次闭环稳定性测试。我们方法的可行性通过在真实测试场景中跟踪多个角度的轮廓来说明。对于轨迹或多个设定点的跟踪，我们分别获得了大约 0.6545 和 0.8651 度的平均误差。还显示了将传统拖拉机转换为基本自主农业越野拖拉机 (AAOT) 的一些机电一体化集成。