کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
381534 1437489 2009 16 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Stable adaptive control with recurrent neural networks for square MIMO non-linear systems
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Stable adaptive control with recurrent neural networks for square MIMO non-linear systems
چکیده انگلیسی

In this paper, stable indirect adaptive control with recurrent neural networks is presented for square multivariable non-linear plants with unknown dynamics. The control scheme is made of an adaptive instantaneous neural model, a neural controller based on fully connected “Real-Time Recurrent Learning” (RTRL) networks and an online parameters updating law. Closed-loop performances as well as sufficient conditions for asymptotic stability are derived from the Lyapunov approach according to the adaptive updating rate parameter. Robustness is also considered in terms of sensor noise and model uncertainties. The control scheme is then applied to the Tennessee Eastman Challenge Process in order to illustrate the efficiency of the proposed method for real-world control problems.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering Applications of Artificial Intelligence - Volume 22, Issues 4–5, June 2009, Pages 702–717
نویسندگان
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