Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Siamak Azargoshasb"'
Publikováno v:
مهندسی مخابرات جنوب, Vol 12, Iss 46, Pp 77-91 (2024)
In this paper, a robust dynamic slip mode controller for an electrical robot manipulator is presented. The control law calculates the motor voltage based on the voltage control strategy. Uncertainties are estimated using the Fourier series expansion
Externí odkaz:
https://doaj.org/article/b3a3669733644e6491168ad412c2c705
Publikováno v:
مهندسی مخابرات جنوب, Vol 12, Iss 45, Pp 75-91 (2024)
In this paper, a new method for robust control is used. The whole robotic system, including the robot arm and motors in control, is considered. The main purpose of this article is to obtain the best results of the control law in order to achieve the
Externí odkaz:
https://doaj.org/article/aecb481f711c427c8f6faba024b332ac
Publikováno v:
International Journal of Intelligent Computing and Cybernetics. 7:382-396
Purpose – The purpose of this paper is to design a discrete indirect adaptive fuzzy controller for a robotic manipulator. This paper addresses how to overcome the approximation error of the fuzzy system and uncertainties for asymptotic tracking con
Publikováno v:
Nonlinear Dynamics. 78:2195-2204
This paper presents a novel discrete adaptive fuzzy controller for electrically driven robot manipulators. It addresses how to overcome the nonlinearity, uncertainties, discretizing error and approximation error of the fuzzy system for asymptotic tra
Publikováno v:
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering. 33:1051-1067
Purpose – Discrete control of robot manipulators with uncertain model is the purpose of this paper. Design/methodology/approach – The proposed control design is model-free by employing an adaptive fuzzy estimator in the controller for the estimat
Publikováno v:
Journal of Artificial Intelligence and Data Mining, Vol 3, Iss 1, Pp 113-120 (2015)
This paper presents a discrete-time robust control for electrically driven robot manipulators in the task space. A novel discrete-time model-free control law is proposed by employing an adaptive fuzzy estimator for the compensation of the uncertainty