Optimized UAV Control: Evaluating SMC and SMC-Based Backstepping Strategies

This paper presents a comprehensive comparative analysis of Sliding Mode Control (SMC) and SMC-based back stepping Control for an Unmanned Aerial Vehicle (UAV) type quadrotor. The study evaluates both control strategies' performance, robustness, and efficiency in handling the dynamics of a quadrotor UAV. The UAV's complex dynamics and under actuated nature pose significant challenges, necessitating robust control techniques to ensure stability and accurate trajectory tracking.We first outline the fundamental principles of SMC and its implementation for quadrotor control. Subsequently, we introduce the Back stepping approach and its integration with SMC, highlighting the theoretical enhancements expected from this combination. Both control methods are then rigorously tested through simulations under various scenarios, including disturbances and model uncertainties.Simulation outcomes indicate that the integrated SMC-based Back stepping Control method delivers notably superior performance compared to the traditional SMC approach. Specifically, it achieves a reduction of up to 85% in roll angle error, a 66.7% improvement in altitude tracking, and approximately 60% error reduction along both the X and Y axes. Furthermore, the hybrid controller exhibits quicker recovery from external disturbances and enhanced robustness in the presence of system uncertainties.This comparative analysis underscores the potential benefits of integrating Back stepping techniques with traditional SMC for UAV applications, offering insights into their practical implications for advanced UAV control systems.

Authors

Institutions

Publication Details

Published
2025-05-14
DOI
https://doi.org/10.1109/sist61657.2025.11139207
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimized UAV Control: Evaluating SMC and SMC-Based Backstepping Strategies

Hüseyin Canbolat, Adil K. Maidanov, Sabyrzhan Atanov
Adaptive Control of Nonlinear Systems
article

Optimized UAV Control: Evaluating SMC and SMC-Based Backstepping Strategies

Hüseyin Canbolat, Adil K. Maidanov, Sabyrzhan Atanov
article en

Abstract

This paper presents a comprehensive comparative analysis of Sliding Mode Control (SMC) and SMC-based back stepping Control for an Unmanned Aerial Vehicle (UAV) type quadrotor. The study evaluates both control strategies' performance, robustness, and efficiency in handling the dynamics of a quadrotor UAV. The UAV's complex dynamics and under actuated nature pose significant challenges, necessitating robust control techniques to ensure stability and accurate trajectory tracking.We first outline the fundamental principles of SMC and its implementation for quadrotor control. Subsequently, we introduce the Back stepping approach and its integration with SMC, highlighting the theoretical enhancements expected from this combination. Both control methods are then rigorously tested through simulations under various scenarios, including disturbances and model uncertainties.Simulation outcomes indicate that the integrated SMC-based Back stepping Control method delivers notably superior performance compared to the traditional SMC approach. Specifically, it achieves a reduction of up to 85% in roll angle error, a 66.7% improvement in altitude tracking, and approximately 60% error reduction along both the X and Y axes. Furthermore, the hybrid controller exhibits quicker recovery from external disturbances and enhanced robustness in the presence of system uncertainties.This comparative analysis underscores the potential benefits of integrating Back stepping techniques with traditional SMC for UAV applications, offering insights into their practical implications for advanced UAV control systems.

L. N. Gumilyov Eurasian National University (KZ), Ankara University (TR)
Openalex Percentile: Top 72%
Adaptive Control of Nonlinear Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.