مهندسی مکانیک مدرس

مهندسی مکانیک مدرس

کنترل ردیابی شبکه‌ی عصبی موجک تطبیقی یک ربات تک لینک با ورودی لقی

نویسندگان
سپیده عیسی پور 1
ابوالفضل رنجبر نوعی 2
سید جلیل ساداتی رستمی 3
1 دانشکده مهندسی برق و کامپیوتر، دانشگاه صنعتی نوشیروانی بابل، بابل، ایران
2 دانشگاه صنعتی نوشیروانی بابل
3 عضو هیئت علمی دانشکده برق و کامپیوتر- دانشگاه صنعتی نوشیروانی بابل
چکیده
در این مقاله یک کنترل کننده ردیابی مبتنی بر شبکه عصبی ویولت تطبیقی، برای حل مشکل پایداری و کنترل کلاسی از سیستمهای غیرخطی نامعین زمان-گسسته مورد بررسی قرار گرفته است. سیستم مورد مطالعه به فرم پسخورد اکید بوده و شامل غیرخطی لقی و اغتشاش خارجی می باشد و غیرخطی لقی به شکل نامتقارن در نظر گرفته شده است. این سیستمها حالت کلی تری نسبت به سیستمهای مورد مطالعه پیشین دارد و برای غلبه بر پیچیدگی پایداری آن، با استفاده از توابع پیش‌بین، به یک سیستم پیش‌بینی کننده n گام پیش رو تبدیل شده است. در اینجا از شبکه‌ی عصبی موجک برای تقریب توابع ناشناخته در سیستم‌های تبدیل شده استفاده می‌شود. قوانین تطبیق بر اساس قاعده‌ی گرادیان نزولی، برای بروزرسانی وزنهای شبکه عصبی موجک و جبران اثر پارامترهای نامعلوم لقی طراحی می‌شود. بر اساس تئوری لیاپانوف نشان داده می شود که همه ی سیگنالها در سیستم حلقه بسته کراندار بوده و خطای ردیابی به همسایگی کوچکی از صفر همگرا می شود. روش ارائه شده در این مقاله، بر روی یک سیستم روبات با یک بازوی مکانیکی متحرک شبیه سازی شده است و در پایان، به منظور اعتبارسنجی، نتایج روش پیشنهادی با نتایج اعمال دو کنترل‌کننده PID و مد لغزشی، مورد مقایسه قرار گرفته است.
کلیدواژه‌ها
کنترل تطبیقی ردیابی
شبکه عصبی موجک
ورودی غیر خطی لقی
سیستم غیرخطی زمان گسسته
ربات تک لینک

موضوعات

عنوان مقاله English

Adaptive Wavelet Neural Network Tracking Control of a Single-Link Robot with Backlash Input

نویسندگان English

Sepideh Esapour 1
Abolfazl Ranjbar N. 2
1 Electrical and Computer engineering department, Babol Noshirvani Universality of Technology, Babol, Iran
2 Babol Noshirvani University of Technology
چکیده English

In this paper, an adaptive wavelet neural network tracking controller is studied for solving control and stability problem of a class of uncertain nonlinear systems. The considered systems in this paper are of the discrete-time form in pure-feedback structure and include the backlash and external disturbance. The backlash nonlinearity input appears non-symmetric in the systems. These systems are more general than those in the previous work. There are major difficulties for stabilizing such systems and in order to overcome the difficulties, by using prediction function of future states, the systems are transformed into an n-step-ahead predictor. The wavelet neural networks are used to approximate the unknown functions and unknown backlash in the transformed systems and the adaption laws are to update neural weights and to compensate for the unknown parameter of backlash. Based on the Lyapunov theory, it is shown that the proposed controller guarantees that all the signals in the closed-loop system are bounded and the tracking error converges to a small neighborhood of zero. The simulation of a Single-link robot arm system is provided to verify the effectiveness of the control approach in the paper. Finally, in order to validate, the results of the proposed method are compared with the results of PID and sliding mode controller.

کلیدواژه‌ها English

Adaptive Tracking control
Wavelet Neural Network
Backlash Nonlinear input
Nonlinear Discrete-time systems
Single Link Robot
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مهندسی مکانیک مدرس
دوره 18، شماره 8
آذر 1397
صفحه 37-44