Model reference adaptive control based on a self-recurrent wavelet neural network utilizing micro artificial immune systems
العناوين الأخرى
نظام سيطرة متكيف ذو موديل مرجعي مبني على شبكة عصبية مويجية ذاتية التكرار باستخدام أنظمة المناعة الصناعية الدقيقة
المؤلفون المشاركون
Lutfi, Umar Faruq
Dawud, Maryam Hasan
المصدر
al-Khwarizmi Engineering Journal
العدد
المجلد 13، العدد 2 (30 يونيو/حزيران 2017)، ص ص. 107-122، 16ص.
الناشر
جامعة بغداد كلية هندسة الخوارزمي
تاريخ النشر
2017-06-30
دولة النشر
العراق
عدد الصفحات
16
التخصصات الرئيسية
العلوم الهندسية والتكنولوجية (متداخلة التخصصات)
الملخص EN
This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems.
The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN).
In particular, this improvement was achieved by adopting two modifications to the original WNN structure.
These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer.
Furthermore, an on-line training procedure was proposed to enhance the control performance of the SRWNN-based MRAC.
As the training method, the recently developed modified micro artificial immune system (MMAIS) was used to optimize the parameters of the SRWNN.
The effectiveness of this control approach was demonstrated by controlling several nonlinear dynamical systems.
For each of these systems, several evaluation tests were conducted, including control performance tests, robustness tests, and generalization tests.
From these tests, the SRWNN-based MRAC has exhibited its effectiveness regarding accurate control, disturbance rejection, and generalization ability.
In addition, a comparative study was made with other related controllers, namely the original WNN, the artificial neural network (ANN), and the modified recurrent network (MRN).
The results of these comparison tests indicated the superiority of the SRWNN controller over the other related controllers.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Lutfi, Umar Faruq& Dawud, Maryam Hasan. 2017. Model reference adaptive control based on a self-recurrent wavelet neural network utilizing micro artificial immune systems. al-Khwarizmi Engineering Journal،Vol. 13, no. 2, pp.107-122.
https://search.emarefa.net/detail/BIM-838197
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Lutfi, Umar Faruq& Dawud, Maryam Hasan. Model reference adaptive control based on a self-recurrent wavelet neural network utilizing micro artificial immune systems. al-Khwarizmi Engineering Journal Vol. 13, no. 2 (2017), pp.107-122.
https://search.emarefa.net/detail/BIM-838197
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Lutfi, Umar Faruq& Dawud, Maryam Hasan. Model reference adaptive control based on a self-recurrent wavelet neural network utilizing micro artificial immune systems. al-Khwarizmi Engineering Journal. 2017. Vol. 13, no. 2, pp.107-122.
https://search.emarefa.net/detail/BIM-838197
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
رقم السجل
BIM-838197
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر