Backstepping and Sliding-mode Techniques Applied to an Indoor Micro Quadrotor

By Samir Bouabdallah, Roland Yves Siegwart. Proceedings of the 2005 IEEE International Conference on Robotics and Automation, 2005

1,168 citations recorded by the source corpus.

The latest technological progress in sensors, actuators and energy storage devices enables the developments of miniature VTOL systems. In this paper we present the results of two nonlinear control techniques applied to an autonomous micro helicopter called Quadrotor. A backstepping and a sliding-mode techniques. We performed various simulations in open and closed loop and implemented several experiments on the test-bench to validate the control laws. Finally, we discuss the results of each approach. These developments are part of the OS4 project in our lab.

Subfields: Computer Networks and Communications, Control and Systems Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/f1e997e22260ca0ef8b3f942660c68bfe2e5dd52

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Citations in the corpus

Nonlinear robust tracking control of a quadrotor UAV on SE(3) (2011, neutral): “Several nonlinear controllers have been developed, by using backstepping [1], sliding mode technique [2], nonlinear H∞ contorller [3], and adaptive neural network [4].”
The Trajectory Tracking Problem of Quadrotor UAV: Global Stability Analysis and Control Design Based on the Cascade Theory (2014, background): “Some works have dealt with the position or trajectory tracking control problem of the quadrotor, such as the backstepping and sliding mode control [9], feedback linearization and sliding mode control [10], backstepping-based nonlinear control [11], robust adaptive control [12], modified PID control ”
Using Task Descriptions in Lifelong Machine Learning for Improved Performance and Zero-Shot Transfer (2017, methodology): “To ensure realistic dynamics, we use the model of Bouabdallah and Siegwart (2005), which has been veriﬁed on physical systems.”
Modeling and PD Control of a Quadrotor VTOL Vehicle (2007, background): “S. Bouabdallah et. al. mechanically designed, dynamically modeled and used nonlinear control techniques in their works [18, 19].”
A survey of quadrotor Unmanned Aerial Vehicles (2012, background): “Various control structures ranging from basic PID controllers [15, 27, 62] to more complex systems using backstepping or neural networks [16, 26, 46] have proved to be efficient.”
Vision based MAV navigation in unknown and unstructured environments (2010, methodology): “[4] analyzed the application of two different control techniques ”Sliding-Mode” and ”Backstepping” and especially showed that the later has very good stabilizing qualities.”
Real-time stabilization of a small three-rotor aircraft (2008, background): “Early UAVs were developed just after the end of the Second World War but since then, very little has been done on the development of new configurations.”
design and control of quadrotors with application to autonomous flying (2007, methodology): “This time, we were able to elegantly reject strong disturbances, but the stabilization in hover flight was delicate, this is detailed in paper [4].”
Onboard IMU and monocular vision based control for MAVs in unknown in- and outdoor environments (2011, result): “This has already been discussed in previous work [17], [7].”
Monocular‐SLAM–based navigation for autonomous micro helicopters in GPS‐denied environments (2011, background): “Bouabdallah and Siegwart (2005) analyzed the application of two different control techniques— " sliding-mode " and " backstepping " — and showed that the latter has particularly good stabilizing qualities.”
Full control of a quadrotor (2007, methodology): “This time, we were able to elegantly reject strong disturbances but the stabilization in hover flight was delicate (see [8]).”
Learning Transferable Knowledge Through Embedding Spaces (2019, methodology): “To ensure realistic dynamics, we use the model of Bouabdallah and Siegwart [196], which has been verified on physical systems.”