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All Journal IAES International Journal of Robotics and Automation (IJRA) Bulletin of Electrical Engineering and Informatics
Shahrum Shah Abdullah
Universiti Teknologi Malaysia
Automotive Engineering Electrical & Electronics Engineering

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Depth Level Control System using Peripheral Interface Controller for Underwater Vehicle Muhamad Fadli Ghani; Shahrum Shah Abdullah
IAES International Journal of Robotics and Automation (IJRA) Vol 2, No 2: June 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (310.829 KB) | DOI: 10.11591/ijra.v2i2.pp69-72

Abstract

This research explained on a design and development of an Automatic Depth Control System for underwater vehicle. Definition of underwater vehicle is a robotic sub-sea that is a part of the emerging field of autonomous and unmanned vehicles. This project shows the implementation’s development of an Automatic Depth Control System on a test prototyping vehicle especially involved small-scale and low cost sub-sea robots. The Automatic Depth Control System assembled with mechanical system and module of electronic system for development of a controller.
Adaptive infill sampling strategy for metamodeling: Challenge and future research directions Che Munira Che Razali; Shahrum Shah Abdullah; Amir Parnianifard; Amrul Faruq
Bulletin of Electrical Engineering and Informatics Vol 9, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (515.189 KB) | DOI: 10.11591/eei.v9i5.2162

Abstract

The widespread use of computer experiments for design optimization has made the issue of reducing computational cost, improving accuracy, removing the “curse of dimensionality” and avoiding expensive function approximation becoming even more important. Metamodeling also known as surrogate modeling, can approximate the actual simulation model allowing for much faster execution time thus becoming a useful method to mitigate these problems. There are two (2) well-known metamodeling techniques which is kriging and radial basis function (RBF) discussed in this paper based on widely used algorithm tool from previous work in modern engineering design of optimization. An integral part of metamodeling is in the method to sample new data from the actual simulation model. Sampling new data for metamodeling requires finding the location (or value) of one or more new data such that the accuracy of the metamodel can be increased as much as possible after the sampling process. This paper discussed the challenges of adaptive sampling in metamodel and proposed an ensemble non-homogeneous method for best model voting to obtain new sample points.
Co-Authors Amir Parnianifard Amrul Faruq Che Munira Che Razali Muhamad Fadli Ghani