کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10136187 | 1645681 | 2018 | 18 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Neural network-based target tracking control of underactuated autonomous underwater vehicles with a prescribed performance
ترجمه فارسی عنوان
کنترل ردیابی هدف مبتنی بر شبکه عصبی از وسایل نقلیه زیر زمینی خود مستقل با عملکرد پیشنهادی
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی دریا (اقیانوس)
چکیده انگلیسی
In this paper, the target tracking control problem is addressed for underactuated autonomous underwater vehicles (AUV) with a prescribed performance. For this purpose, the range and bearing angles of the AUV relative to an underwater target are transformed to a second-order open-loop error dynamic model by using the prescribed performance bound technique. Then, a new tracking controller is proposed such that the tracking errors converge to an arbitrary small ultimate bound and their transient performance are guaranteed with a pre-specified maximum overshoot and the convergence rate. To overcome unmodeled dynamics and external disturbances that are imposed on the vehicle by the wind, waves, and ocean currents, a multi-layer neural network and an adaptive robust controller are adopted. A Lyapunov stability synthesis shows that all signals of the control system are bounded, and tracking errors converge to a small region containing the origin with a prescribed performance. Finally, simulations are performed in MATLAB software and a comparative study verifies the theoretical results.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ocean Engineering - Volume 167, 1 November 2018, Pages 239-256
Journal: Ocean Engineering - Volume 167, 1 November 2018, Pages 239-256
نویسندگان
Omid Elhaki, Khoshnam Shojaei,