A master's thesis at the College of Engineering at the University of Basrah searched (a fuzzy immune control system to follow the path of an arm) by the student "Wood Idris Shatnan"

The thesis dealt with the study of the topic of the artificial immune system and it was used as an improvement tool called the clonal selection algorithm and as a control method.

In the first model, the artificial immune system optimization tool is used to improve the proposed control values ​​to track the trajectory of the robot arm. In this approach, four different control systems were proposed and the elements of these methods were improved using the clonal selection algorithm.

As for the second model, the immune system with fuzzy logic and exponential derivational integrative control was proposed, the immune system with fuzzy logic and exponential derivational integrative control was proposed as a control method to track the trajectory of the robot arm, and the elements of this structure were improved using the clonal selection algorithm. This controller was applied to the robot with Two grades, and comparing the performance of this control with the relative integrative fuzzy immune system derived, the robustness test showed good results.

And the goal of the thesis is to suggest an efficient control scheme for tracking the trajectory of the robot arm based on the use of the artificial immune system and fuzzy logic. Finally, the best method from the previous methods of the three-degree robot was highlighted. The goal of the control structures is to make the robot arm follow the given path under different load values.

The message concluded good tracking performance under different loading conditions and uncertainty model. The results also showed that the robot followed all tracks correctly, with less error and more solidity using different control methods.