Dimitrios Pentaris, "Control of Robotic Arm using Neuro-fuzzy Systems", Diploma Work, School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece, 2022
https://doi.org/10.26233/heallink.tuc.92513
Intelligent mechanical systems, which are equipped with sensors and exciters made of piezoelectric materials, interact with the environment through an active control mechanism. One such example is the case of a robotic arm. However, due to imperfections in the mechanical model, but also in the sensory organs, a certain degree of uncertainty always enters the system. Classic control can operate under conditions of uncertainty, but with reduced efficiency.Designing nonlinear feedback control rules using classical methods is a difficult task. It is therefore recommended to use intelligent control techniques, which are based on neurofuzzy systems.The aim of this work is the development of a reliable neurofuzzy control system in MATLAB (Simulink) environment and its connection to a mechanical robotic arm system of 2 degrees of freedom. The techniques that will be developed in the context of this work are suitable for solving linear and non-linear systems and can be applied in a numeral of different applications.