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گواهی نمایه سازی مقاله Online Multivariable Identification and Adaptive Self-tuning PID Control of a Flying Boat System Using Neural Networks

عنوان مقاله: Online Multivariable Identification and Adaptive Self-tuning PID Control of a Flying Boat System Using Neural Networks
شناسه (COI) مقاله: NSMI12_056
منتشر شده در دوازدهمین همایش ملی صنایع دریایی ایران در سال ۱۳۸۹
مشخصات نویسندگان مقاله:

Seyyed mehdi anvar - Marine Industries Organization, Shiraz, Iran
Amin Sabet Kamalabady - Petroleum University of Technology (PUT), Tehran
Dariush ahmadzadeh - 3Marine Industries Organization, Shiraz, Iran

خلاصه مقاله:
In this paper, a new approach is proposed for online identification of the dynamics of a flying boat system based on neural networks (NNs). Moreover, a new NN-based self-tuning PID control scheme is developed for the purpose of the adaptive control of nonlinear systems. The neural network employed for this purpose is one of the novel ones called Growing and Pruning Radial Basis Function (GAP-RBF). The Extended Kalman Filter (EKF) learning algorithm is utilized for parameter updating in the GAP-RBF neural network. The proposed identification approach is applied to a multi-input, multi-output flying boat system, and its performance is evaluated. The obtained results show the excellent performance of the proposed scheme in exact modeling of the system.

کلمات کلیدی:
GAP-RBF, EKF, PID, flying boat

صفحه اختصاصی مقاله و دریافت فایل کامل: http://www.civilica.com/Paper-NSMI12-NSMI12_056.html