Next Article in Journal
Canopy Composition and Spatial Configuration Influences Beta Diversity in Temperate Regrowth Forests of Southeastern Australia
Next Article in Special Issue
Attitude Fault-Tolerant Control of Aerial Robots with Sensor Faults and Disturbances
Previous Article in Journal
A Motion-Aware Siamese Framework for Unmanned Aerial Vehicle Tracking
Previous Article in Special Issue
Adaptive Fault-Tolerant Tracking Control of Quadrotor UAVs against Uncertainties of Inertial Matrices and State Constraints
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Drones
Volume 7
Issue 3
10.3390/drones7030154
drones-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Integral Backstepping Sliding Mode Control for Unmanned Autonomous Helicopters Based on Neural Networks

by
Min Wan
1,
Mou Chen
1,* and
Mihai Lungu
2,3
1
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
2
Faculty of Electrical Engineering, University of Craiova, 200692 Craiova, Romania
3
Aerospace Engineering Doctoral School, University Politehnica of Bucharest, 060042 Bucharest, Romania
*
Author to whom correspondence should be addressed.
Drones 2023, 7(3), 154; https://doi.org/10.3390/drones7030154
Submission received: 11 January 2023 / Revised: 14 February 2023 / Accepted: 18 February 2023 / Published: 22 February 2023
(This article belongs to the Special Issue Advanced Intelligent Decision-Making and Flight Control of Unmanned Aerial Vehicles)
Browse Figures
Versions Notes

Abstract

In this paper, we propose an adaptive control approach to deal with the problems of input saturation, external disturbances, and uncertainty in the unmanned autonomous helicopter system. The dynamics of the system take into account the presence of input saturation, uncertainty, and external disturbances. Auxiliary systems are built to handle the input saturation. The neural networks are applied to approximate the uncertain terms. The control scheme combining integral backstepping and sliding mode control is developed in position and attitude subsystems, respectively. In the closed-loop system, the boundedness of the signals is proved by means of the Lyapunov theory. The simulation demonstrates that the approach has good robustness and tracking performance.
Keywords: unmanned autonomous helicopter; integral backstepping; neural networks; sliding mode control unmanned autonomous helicopter; integral backstepping; neural networks; sliding mode control

Share and Cite

MDPI and ACS Style

Wan, M.; Chen, M.; Lungu, M. Integral Backstepping Sliding Mode Control for Unmanned Autonomous Helicopters Based on Neural Networks. Drones 2023, 7, 154. https://doi.org/10.3390/drones7030154

AMA Style

Wan M, Chen M, Lungu M. Integral Backstepping Sliding Mode Control for Unmanned Autonomous Helicopters Based on Neural Networks. Drones. 2023; 7(3):154. https://doi.org/10.3390/drones7030154

Chicago/Turabian Style

Wan, Min, Mou Chen, and Mihai Lungu. 2023. "Integral Backstepping Sliding Mode Control for Unmanned Autonomous Helicopters Based on Neural Networks" Drones 7, no. 3: 154. https://doi.org/10.3390/drones7030154

APA Style

Wan, M., Chen, M., & Lungu, M. (2023). Integral Backstepping Sliding Mode Control for Unmanned Autonomous Helicopters Based on Neural Networks. Drones, 7(3), 154. https://doi.org/10.3390/drones7030154

Article Metrics

Back to TopTop