This paper proposes an adaptive fuzzy-neural inference system (ANFIS)-based control approach for a six degrees of freedom (6-DoF) robotic manipulator. Its main objective is to …
S Khorashadizadeh, M Sadeghijaleh - Computers & Electrical Engineering, 2018 - Elsevier
This paper presents a model-free controller for robot manipulators driven by permanent magnet synchronous motors (PMSM). The contribution of this paper is merging the electrical …
In this paper, a new method for secure communication based on chaos synchronization is proposed. It is consisted of a state feedback controller and a robust control term using the …
L Pan, G Bao, F Xu, L Zhang - Assembly Automation, 2018 - emerald.com
Purpose This paper aims to present an adaptive robust sliding mode tracking controller for a 6 degree-of-freedom industrial assembly robot with parametric uncertainties and external …
SM Ahmadi, MM Fateh - International Journal of Control, 2019 - Taylor & Francis
An uncertainty estimation and compensation can improve the performance of control systems due to structured and unstructured uncertainty. This paper presents a robust task …
R Yang, C Yang, M Chen, ASK Annamalai - Neurocomputing, 2017 - Elsevier
In this paper, a novel optimal adaptive radial basis function neural network (RBFNN) control has been investigated for a class of multiple-input-multiple-output (MIMO) nonlinear robot …
In this study, a new controller for chaos synchronization is proposed. It consists of a state feedback controller and a robust control term using Legendre polynomials to compensate for …
S Khorashadizadeh, M Mahdian - 2016 4th international …, 2016 - ieeexplore.ieee.org
This paper presents an intelligent controller for voltage tracking control of DC-DC boost converters. The control law is a brain emotional learning based intelligent controller …