Tuning PID controller by neural network for robot manipulator trajectory tracking
Other Title(s)
موالفة المسيطر التناسبي-التكاملي-التفاضلي بالشبكة العصبية لتتبع مسار ذراع روبوت
Author
Source
al-Khwarizmi Engineering Journal
Issue
Vol. 9, Issue 1 (31 Mar. 2013), pp.19-28, 10 p.
Publisher
University of Baghdad al-Khwarizmi College of Engineering
Publication Date
2013-03-31
Country of Publication
Iraq
No. of Pages
10
Main Subjects
Topics
Abstract AR
اقترح الباحثان Ziegler و Nichols طريقة لتوليف معاملات المسيطرPID.
الطريقة بسيطة و تعطي قيم ثابتة للمعاملات مما يجعل المسيطر PID ضعيفا في التكيف للتغير في خواص المنظومة و ظروف التشغيل.
لكي ينجز مسيطر متكيف، تم اقتراح في هذا البحث موالفة المسيطر PID بالشبكة العصبية (NN) و الذي يجمع المسيطر PID التقليدي مع قابلية التعلم للشبكة العصبية.
إن معاملات المسيطر PID و هي المكاسب KP، KI، KD التقليدي لذراع الروبوت بالمسيطر المقترح لكي ينجز تتبع المسار بأقل خطأ و تحسين التصرف الديناميكي (تجاوز الحد).
استخدمت المماثلة عبر الحاسوب الآلي و أظهرت النتائج أن المسيطر المقترح يمتلك تكيفا ذاتيا متفوقا على المسيطر PID التقليدي.
Abstract EN
Ziegler and Nichols proposed the well-known Ziegler-Nichols method to tune the coefficients of PID controller.
This tuning method is simple and gives fixed values for the coefficients which make PID controller have weak adaptabilities for the model parameters variation and changing in operating conditions.
In order to achieve adaptive controller, the Neural Network (NN) self-tuning PID control is proposed in this paper which combines conventional PID controller and Neural Network learning capabilities.
The proportional, integral and derivative (KP, KI, KD) gains are self tuned on-line by the NN output which is obtained due to the error value on the desired output of the system under control.
The conventional PID controller in the robot manipulator is replaced by NN self-tuning PID controller so as to achieve trajectory tracking with minimum steady-state error and improving the dynamic behavior (overshoot).
The simulation results showed that the proposed controller has strong self-adaptability over the conventional PID controller.
American Psychological Association (APA)
al-Khayyat, Sad Zaghlul Said. 2013. Tuning PID controller by neural network for robot manipulator trajectory tracking. al-Khwarizmi Engineering Journal،Vol. 9, no. 1, pp.19-28.
https://search.emarefa.net/detail/BIM-322818
Modern Language Association (MLA)
al-Khayyat, Sad Zaghlul Said. Tuning PID controller by neural network for robot manipulator trajectory tracking. al-Khwarizmi Engineering Journal Vol. 9, no. 1 (2013), pp.19-28.
https://search.emarefa.net/detail/BIM-322818
American Medical Association (AMA)
al-Khayyat, Sad Zaghlul Said. Tuning PID controller by neural network for robot manipulator trajectory tracking. al-Khwarizmi Engineering Journal. 2013. Vol. 9, no. 1, pp.19-28.
https://search.emarefa.net/detail/BIM-322818
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 26-27
Record ID
BIM-322818