طراحی کنترل‌کننده تحمّل‌پذیر عیب مقاوم مبتنی‌‌بر شبکه عصبی برای فضاپیما

فروتن, علی; غزل, میلاد; مومنی, ,وحید

doi:10.22034/jtae.2025.9.4.1

طراحی کنترل‌کننده تحمّل‌پذیر عیب مقاوم مبتنی‌‌بر شبکه عصبی برای فضاپیما

نوع مقاله : علمی پژوهشی

نویسندگان

علی فروتن ¹

میلاد غزل ²

,وحید مومنی ³

¹ کارشناسی‌ارشد، گروه مهندسی برق، دانشکده مهندسی، دانشگاه گلستان، گرگان، ایران

² استادیار، گروه مهندسی برق، دانشگاه صنعتی امیرکبیر، تهران، ایران

³ دانشجوی دکتری، گروه مهندسی برق، دانشگاه تربیت مدرس، تهران، ایران

10.22034/jtae.2025.9.4.1

چکیده

در این مقاله یک کنترل‌کننده مقاوم تحمّل‌پذیر عیب مبتنی بر شبکه عصبی مصنوعی به‌منظور کنترل وضعیت سیستم غیر‌خطی فضاپیما در حضور نامعینی‌های دینامیک سیستم، نویز، اغتشاش‌های خارجی وارد بر سیستم و عیب عملگر‌ها پیشنهاد می‌گردد. با بهره‌گیری از شبکه عصبی، دینامیک غیر‌خطی سیستم تخمین زده می‌شود و در طراحی کنترل‌کننده مقاوم پیشنهادی مورد استفاده قرار می‌گیرد. از مزایای رهیافت پیشنهادی، قابلیت اطمینان بالا، ردیابی دقیق مسیر، خطای ردیابی ‌کوچک، سرعت همگرایی، قوام و عملکرد مناسب سیستم کنترل در حضور عدم قطعیت‌های دینامیک سیستم، عیب و خرابی عملگر‌ها و اغتشاش‌های‌ خارجی است. وزن‌های شبکه عصبی به قسمی تنظیم و به‌روز‌رسانی می‌شوند که مشتق تابع لیاپانوف منفی و پایداری سیستم حلقه بسته تضمین گردد. در سناریو‌های مختلف عیب عملگر‌ها، عملکرد کنترل‌کننده پیشنهادی با سایر کنترل‌کننده‌ها مورد قیاس قرار گرفته‌است.

کلیدواژه‌ها

کنترل‌کننده تحمل‌پذیر عیب

کنترل‌کننده مدل آزاد

کنترل مد لغزشی مقاوم

شبکه عصبی

موضوعات

مکانیک پرواز/ناوبری/کنترل/...

عنوان مقاله English

Design a Robust Fault Tolerant Control Based on Neural Network forSpacecraft

نویسندگان English

Ali Foroutan ¹

Milad Ghazal ²

Vahid Momeni ³

¹ Department of Electrical Engineering, Faculty of Engineering, Golestan University, Gorgan, Iran

² Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran

³ Department of Electrical Engineering, Tarbiat Modares University, Tehran, Iran

چکیده English

In this article, a robust fault-tolerant controller based on artificial neural networks is introduced for attitude regulation of a nonlinear spacecraft system under system dynamic uncertainties, measurement noise, external disturbances, and actuator faults. Using neural networks, the spacecraft's nonlinear dynamics are approximated and incorporated into the development of the robust control scheme. The proposed method offers enhanced reliability, precise trajectory tracking, minimal tracking error, rapid convergence, robustness, and consistent control performance despite dynamic uncertainties, actuator malfunctions, and external perturbations. Neural network weights are adapted and updated to ensure that the Lyapunov function’s derivative remains negative, thereby guaranteeing closed-loop system stability. The controller’s performance is assessed under multiple actuator fault scenarios and benchmarked against alternative control strategies.

کلیدواژه‌ها English

Fault tolerant control

Model free controller

Robust sliding mode control

Neural network

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