Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Arfah Syahida Mohd Nor"'
Autor:
‘Ain Eazriena Che Man, Suzanna Ridzuan Aw, Nazry Abd Rahman, Raja Siti Nur Adiimah Raja Aris, Lia Safiyah Syafie, Mohd Hafiz Othman, Arfah Syahida Mohd Nor, Nur A’in Izzati Shuhaimi
Publikováno v:
Journal of Physics: Conference Series. 2319:012012
A grass cutter is a machine that uses a revolving blade or blades to cut a lawn grass. Many designs have been made, each suited to a particular purpose and this robot used string trimmer as the cutting blade. This robot is designed to operate by a re
Autor:
Fadilah Abdul Azis, Lim Wee Teck, Ahmad Fadzli Nizam Abdul Rahman, Mohd Shahrieel Mohd Aras, Shahrum Abdullah, Norhaslinda Hasim, Arfah Syahida Mohd Nor
Publikováno v:
Jurnal Teknologi. 74
This paper investigates the depth control of an unmanned underwater remotely operated vehicle (ROV) using neural network predictive control (NNPC). The NNPC is applied to control the depth of the ROV to improve the performances of system response in
Autor:
Arfah Syahida Mohd Nor, Norhaslinda Hasim, Mohd Shahrieel Mohd Aras, Fadilah Abdul Azis, Lim Wee Teck
Publikováno v:
Jurnal Teknologi. 74
This paper investigates the depth control of an Unmanned Underwater Remotely Operated Vehicle (ROV) based on ballast tank system using conventional PID controller. The PID Controller is applied to control the depth of the ROV from two different refer
Publikováno v:
Scopus-Elsevier
This paper presents the design of an active suspension control of a two–axle railway vehicle using an optimized linear quadratic regulator. The control objective is to minimize the lateral displacement and yaw angle of the wheelsets when the vehicl
Autor:
Shahrum Abdullah, Arfah Syahida Mohd Nor, Mohd Shahrieel Mohd Aras, Kyairul Azmi Baharin, Mohd Khairi Mohd Zambri
Publikováno v:
International Review of Automatic Control (IREACO). 8:149
This paper described the development of modeling of an unmanned underwater vehicle (UUV) using system identification toolbox based on neural network model. The set of data based on neural network model generated by open-loop model of UUV and the inpu