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001-es BibID:BIBFORM105830
Első szerző:Muhammad Maaruf
Cím:Neural Network-based Finite-time Control of Nonlinear Systems with Unknown Dead-zones : Application to Quadrotors / Muhammad Maaruf, Aminu Babangida, Husam A. Almusawi, Peter Szemes Tamas
Dátum:2022
ISSN:2715-5072 2715-5056
Megjegyzések:Over the years, researchers have addressed several control problems of various classes of nonlinear systems. This article considers a class of uncertain strict feedback nonlinear system with unknown external disturbances and asymmetric input dead-zone. Designing a tracking controller for such system is very complex and challenging. This article aims to design a finite-time adaptive neural network backstepping tracking control for the nonlinear system under consideration. In addition, all unknown disturbances and nonlinear functions are lumped together and approximated by radial basis function neural network (RBFNN). Moreover, no prior information about the boundedness of the dead-zone parameters is required in the controller design. With the aid of a Lyapunov candidate function, it has been shown that the tracking errors converge near the origin in finite-time. Simulation results testify that the proposed control approach can force the output to follow the reference trajectory in a short time despite the presence of asymmetric input dead-zone and external disturbances. At last, in order to highlight the effectiveness of the proposed control method, it is applied to a quadrotor unmanned aerial vehicle (UAV).
Tárgyszavak:Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Quadrotor
unmanned aerial vehicle
backstepping control
radial basis function neural network
dead-zone
nonlinear systems
Megjelenés:Journal of Robotics and Control (JRC). - 3 : 6 (2022), p. 735-742. -
További szerzők:Babangida, Aminu (1988-) (Informatics)(mérnök) Almusawi, Husam Abdulkareem (mérnök) Szemes Péter Tamás (1976-) (gépészmérnök, villamosmérnök)
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