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An Improved Design of an Adaptive Sliding Mode Controller for Chattering Attenuation and Trajectory Tracking of the Quadcopter UAV

تصميم محسّن لوحدة تحكم الوضع الانزلاقي التكيفي لتوهين الأحاديث وتتبع مسار الطائرة بدون طيار رباعية المروحيات
Authors: Ahmed Eltayeb; M. F. Rahmat; Mohd Ariffanan Mohd Basri; M. A Mohammed Eltoum; Sami El Ferik;

An Improved Design of an Adaptive Sliding Mode Controller for Chattering Attenuation and Trajectory Tracking of the Quadcopter UAV

Abstract

Los sistemas de vehículos aéreos no tripulados (UAV) de cuadricópteros están recibiendo una atención notable por parte de los investigadores debido a su uso diario en numerosas aplicaciones, particularmente en el momento actual en el que los UAV están desempeñando un papel importante en la lucha contra la pandemia de COVID-19. Este documento se ocupa del problema de la navegación y el control de los UAV en presencia de incertidumbre y perturbaciones externas. Aborda este problema proponiendo un control de modo deslizante adaptativo mejorado (IASMC). La ley de control mejorada genera una ganancia de conmutación adaptativa que logra una rápida adaptación y robustez tanto contra las incertidumbres de los parámetros como contra las perturbaciones externas. Simultáneamente, la ley de control permite mantener un seguimiento robusto de la trayectoria con atenuación del parloteo. El rendimiento del controlador IASMC propuesto se ha evaluado utilizando una plataforma Matlab/Simulink. Los resultados de la simulación obtenidos mostraron que el esquema de control IASMC propuesto como controlador de bucle interno es robusto cuando se trata de incertidumbres y puede rastrear efectivamente las trayectorias deseadas al tiempo que atenúa significativamente el conocido parloteo introducido por el controlador SMC.

Les systèmes de véhicules aériens sans pilote (UAV) Quadcopter reçoivent une attention remarquable de la part des chercheurs en raison de leur utilisation quotidienne dans de nombreuses applications, en particulier à l'heure actuelle où les UAV jouent un rôle important dans la lutte contre la pandémie de COVID-19. Cet article s'intéresse au problème de la navigation et du contrôle des UAV en présence d'incertitudes et de perturbations extérieures. Il aborde cette question en proposant un contrôle adaptatif en mode glissant (IASMC) amélioré. Une loi de commande améliorée génère un gain de commutation adaptatif permettant une adaptation et une robustesse rapides à la fois contre les incertitudes de paramètres et les perturbations externes. Simultanément, la loi de commande permet de maintenir un suivi de trajectoire robuste avec une atténuation du bavardage. Les performances du contrôleur IASMC proposé ont été évaluées à l'aide d'une plate-forme Matlab/Simulink. Les résultats de simulation obtenus ont montré que le schéma de contrôle IASMC proposé en tant que contrôleur de boucle interne est robuste face aux incertitudes et peut suivre efficacement les trajectoires souhaitées tout en atténuant considérablement les bavardages bien connus introduits par le contrôleur SMC.

Quadcopter unmanned aerial vehicles (UAVs) systems are receiving remarkable attention from researchers due to their daily use in numerous applications, particularly at the current time where UAVs are playing a significant role in combating the COVID-19 pandemic. This paper is concerned with the problem of UAV navigation and control in the presence of uncertainty and external disturbances. It addresses this issue by proposing an improved adaptive sliding mode control (IASMC). Improved control law generates an adaptive switching gain achieving fast adaptation and robustness against both parameter uncertainties and external disturbances. Simultaneously, the control law allows for maintaining robust trajectory tracking with chattering attenuation. The performance of the proposed IASMC controller has been evaluated using a Matlab/Simulink platform. The obtained simulation results showed that the proposed IASMC control scheme as an inner loop controller is robust when dealing with uncertainties and can effectively track the desired trajectories while significantly attenuating the well-known chattering introduced by the SMC controller.

تحظى أنظمة الطائرات بدون طيار (UAVs) باهتمام ملحوظ من الباحثين بسبب استخدامها اليومي في العديد من التطبيقات، لا سيما في الوقت الحالي حيث تلعب الطائرات بدون طيار دورًا مهمًا في مكافحة جائحة COVID -19. تهتم هذه الورقة بمشكلة الملاحة والتحكم بالطائرات بدون طيار في وجود عدم اليقين والاضطرابات الخارجية. وهو يعالج هذه المشكلة من خلال اقتراح تحسين التحكم في الوضع الانزلاقي التكيفي (IASMC). يولد قانون التحكم المحسن مكسبًا للتبديل التكيفي يحقق تكيفًا سريعًا وقوة ضد كل من حالات عدم اليقين في المعلمات والاضطرابات الخارجية. في الوقت نفسه، يسمح قانون التحكم بالحفاظ على تتبع مسار قوي مع توهين الثرثرة. تم تقييم أداء وحدة تحكم IASMC المقترحة باستخدام منصة Matlab/Simulink. أظهرت نتائج المحاكاة التي تم الحصول عليها أن مخطط التحكم IASMC المقترح كوحدة تحكم في الحلقة الداخلية قوي عند التعامل مع الشكوك ويمكنه تتبع المسارات المطلوبة بشكل فعال مع تخفيف الثرثرة المعروفة التي أدخلتها وحدة تحكم SMC بشكل كبير.

Keywords

Artificial intelligence, Sliding mode control, SMC control, Astronomy, Robustness (evolution), Sliding Mode Control, Trajectory, Robust control, chattering, Control of Nonholonomic Mobile Robots, adaptive control, Biochemistry, Gene, Adaptive Control, Engineering, General Materials Science, Control system, Control engineering, Physics, General Engineering, Quadcopter UAV, type-2 fuzzy logic, Attenuation, Trajectory Tracking, Chemistry, Aerospace engineering, Computational Theory and Mathematics, Feedback Control, Physical Sciences, Robotic Control and Stabilization Techniques, Electrical engineering. Electronics. Nuclear engineering, MATLAB, General Computer Science, Control (management), Quadcopter, Quantum mechanics, TK Electrical engineering. Electronics Nuclear engineering, Control theory (sociology), Biology, Adaptive Dynamic Programming, Controller (irrigation), Optics, Computer science, Agronomy, TK1-9971, 629, Operating system, Control and Systems Engineering, Electrical engineering, Adaptive Dynamic Programming for Optimal Control, Computer Science, Nonlinear system, PID controller

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
38
Top 10%
Top 10%
Top 10%
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