TY - JOUR
T1 - A bio-inspired global finite time tracking control of four-rotor test bench system
AU - Amin, Rooh ul
AU - Inayat, Irum
AU - Aijun, Li
AU - Shamshirband, Shahaboddin
AU - Rabczuk, Timon
N1 - Publisher Copyright:
Copyright © 2018 Tech Science Press
PY - 2018
Y1 - 2018
N2 - A bio-inspired global finite time control using global fast-terminal sliding mode controller and radial basis function network is presented in this article, to address the attitude tracking control problem of the three degree-of-freedom four-rotor hover system. The proposed controller provides convergence of system states in a predetermined finite time and estimates the unmodeled dynamics of the four-rotor system. Dynamic model of the four-rotor system is derived with Newton’s force equations. The unknown dynamics of four-rotor systems are estimated using Radial basis function. The bio-inspired global fast terminal sliding mode controller is proposed to provide chattering free finite time error convergence and to provide optimal tracking of the attitude angles while being subjected to unknown dynamics. The global stability proof of the designed controller is provided on the basis of Lyapunov stability theorem. The proposed controller is validated by (i) conducting an experiment through implementing it on the laboratory-based hover system, and (ii) through simulations. Performance of the proposed control scheme is also compared with classical and intelligent controllers. The performance comparison exhibits that the designed controller has quick transient response and improved chattering free steady state performance. The proposed bioinspired global fast terminal sliding mode controller offers improved estimation and better tracking performance than the traditional controllers. In addition, the proposed controller is computationally cost effective and can be implanted on multirotor unmanned air vehicles with limited computational processing capabilities.
AB - A bio-inspired global finite time control using global fast-terminal sliding mode controller and radial basis function network is presented in this article, to address the attitude tracking control problem of the three degree-of-freedom four-rotor hover system. The proposed controller provides convergence of system states in a predetermined finite time and estimates the unmodeled dynamics of the four-rotor system. Dynamic model of the four-rotor system is derived with Newton’s force equations. The unknown dynamics of four-rotor systems are estimated using Radial basis function. The bio-inspired global fast terminal sliding mode controller is proposed to provide chattering free finite time error convergence and to provide optimal tracking of the attitude angles while being subjected to unknown dynamics. The global stability proof of the designed controller is provided on the basis of Lyapunov stability theorem. The proposed controller is validated by (i) conducting an experiment through implementing it on the laboratory-based hover system, and (ii) through simulations. Performance of the proposed control scheme is also compared with classical and intelligent controllers. The performance comparison exhibits that the designed controller has quick transient response and improved chattering free steady state performance. The proposed bioinspired global fast terminal sliding mode controller offers improved estimation and better tracking performance than the traditional controllers. In addition, the proposed controller is computationally cost effective and can be implanted on multirotor unmanned air vehicles with limited computational processing capabilities.
KW - Attitude tracking
KW - Bio-inspired global fast terminal sliding mode controller
KW - Four-rotor hover system
KW - Radial basis function network
UR - http://www.scopus.com/inward/record.url?scp=85061864034&partnerID=8YFLogxK
U2 - 10.32604/cmc.2018.03757
DO - 10.32604/cmc.2018.03757
M3 - 文章
AN - SCOPUS:85061864034
SN - 1546-2218
VL - 57
SP - 365
EP - 388
JO - Computers, Materials and Continua
JF - Computers, Materials and Continua
IS - 3
ER -