Trajectory tracking control of A 2-DOF robot arm using neural networks

مقدم أطروحة جامعية

al-Ashi, Mahmud M.

مشرف أطروحة جامعية

al-Aydi, Hatim Ali
Hadrus, Iyad Abu

الجامعة

الجامعة الإسلامية

الكلية

كلية الهندسة

القسم الأكاديمي

قسم الهندسة الكهربائية

دولة الجامعة

فلسطين (قطاع غزة)

الدرجة العلمية

ماجستير

تاريخ الدرجة العلمية

2014

الملخص الإنجليزي

This thesis investigated several control strategies to handle the trajectory tracking problem for a two degree-of-freedom (2-DOF) robotic arm using artificial neural networks (ANNs).

Feed-forward two layer neural networks were designed and utilized in both model-based and non-model based control structures to conduct online learning and identification of the inverse dynamics of the robotic manipulator and to compensate for both structured and unstructured uncertainties.

The simulation results obtained proved the superiority of the proposed neural network controllers to dramatically reduce the error between the desired and actual position trajectories even in the presence of uncertainties unlike other conventional methods such as the PD-computed torque method.

The neural network-based controllers proposed in this thesis provide solutions to the trajectory tracking problem of robotic manipulators with or without a mathematical model which would make them effective controllers for both planned and unplanned trajectory tracking problems for any degree of freedom robotic manipulator.

The development of the mathematical models for the 2-DOF robotic arm and its joints driving motors as well as their simulation experiments were carried out under the Dynamic Modeling Laboratory (Dymola) environment which uses the Modelica object-oriented multi-domain system modeling language.

The simulation results obtained in the thesis were accompanied by three dimensional (3D) figures in order to visualize the results and to help establish a deeper analysis and understanding of these results.

التخصصات الرئيسية

الهندسة الكهربائية

الموضوعات

• أنظمة التحكم
• الروبوتات
• الشبكات العصبية(الحاسبات الإلكترونية)

عدد الصفحات

86

قائمة المحتويات

• APA
• MLA
• AMA

لغة النص

الإنجليزية

نوع البيانات

رسائل جامعية

رقم السجل

BIM-531938