Design of an adaptive control system for optimum soil cultivation in different terrain spectrum with electric unmanned agricultural vehicles (agrobot)

During tillage with electric vehicles, parameters such as soil hardness, stoniness and whether it has been previously processed or not affect the balance of traction, tillage and energy consumption of Agrobots. Especially in inefficient tillage operations, an unoptimized system causes significant losses in battery energy and power draw of the Agrobot. Therefore, it is important for an Agrobot to be able to constantly control the changes that occur between the wheel and tillage equipment and the surface. Therefore, this thesis proposes a new control algorithm based on traction conservation optimization, which is adaptable to changing soil tillage conditions. The proposed control algorithm is called the adaptive control system for tillage (TACS). A cultivator is used as a tillage tool. Optimized control speed is determined by calculating the slip rate that may occur on the wheel during the plunging and pulling of the cultivator, which is the most important parameter of TACS. A traditional PID controller and Fuzzy Logic based model has been developed for optimum shift control. Fuzzy Logic is used to readjust the preset PID gains based on the slip error in tillage. The developed control system was first modeled in the robot operating system (ROS) for the agricultural vehicle Agrobot, which was designed with skid steer drive and performance verification was carried out. Later, the vehicle with skid steer driving capability was produced as a prototype and experimentally verified in real field conditions.