Open AccessFinite‐time super twisting sliding mode controller based on higher‐order sliding mode observer for real‐time trajectory tracking of a quadrotor
Author(s) -
Tripathi Vibhu Kumar,
Kamath Archit Krishna,
Behera Laxmidhar,
Verma Nishchal K.,
Nahavandi Saeid
Publication year - 2020
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2020.0348
Subject(s) - control theory (sociology) , observer (physics) , state observer , sliding mode control , controller (irrigation) , trajectory , lyapunov function , convergence (economics) , mathematics , tracking (education) , computer science , position (finance) , nonlinear system , physics , artificial intelligence , control (management) , psychology , pedagogy , quantum mechanics , astronomy , agronomy , biology , finance , economics , economic growth
The main focus of this study is to develop a finite‐time super‐twisting sliding mode control strategy for the quadrotor based on a higher‐order sliding mode observer (HOSMO). 12 state variables are required to describe the motion of the quadrotor, of which six state variables, namely the position, altitude, and orientation, are assumed to be obtained from the sensors. The remaining state variables, i.e. the linear and angular velocities, are determined using the HOSMO. Besides, the HOSMO aids in determining the unknown bounded lumped disturbances acting on the quadrotor. The output of the HOSMO is utilised for implementing the finite‐time super‐twisting sliding mode controller (FTSTSMC). The proposed FTSTSMC ensures finite‐time convergence of tracking error with chattering attenuation. The chattering analysis for a super‐twisting algorithm is presented in this work. Moreover, the overall system stability is investigated using the Lyapunov theory, and an expression for the time of convergence of the tracking and estimation error is presented. The effectiveness of the proposed methodology is established using numerical simulations and its performance is compared to a finite‐time sliding mode observer coupled with a combination of proportional–integral–derivative and continuous sliding‐mode controller. This is then validated in real‐time using the DJI Matrice 100.