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General Information
Editor-in-chief
Prof. Wael Badawy
Department of Computing and Information Systems Umm Al Qura University, Canada
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.
IJCTE 2015 Vol.7(6): 476-481 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2015.V7.1005

The Performance of Controlling Cannon Barrel Position on the Moving Platform Using Neural Network Control and Sliding Mode Control

Wiwik Wiharti, Santi Anggraini, and Ihsan Lumasa Rimra
Abstract—One of the gunboat weapons that need to stay stable is the cannon. Its unbalance position that caused by pitch and roll disturbance will influence the target accuracy, target detection, tracking system, object identification and the ability to counter the threat. In order to determine this disturbance, the balancing control on the movement platform can be solved by using neural network control and sliding mode control methods. To make an approach, the cannon movement system can be modeled in training and elevation movements and the disturbances are modeled through pitch and roll mechanisms. The variations in obtained parameters of training and elevation (moment of inertia) are the non-linearity result of the moving cannon. The system is simulated to verify the error in the controller’s output processed using the neural network coordination system control and sliding mode control. The learning process in the neural network is made using back propagation method in order to get the weight value at the different disturbances which their results are given in the simulation of coordination models. On the other hand, the free chattering of sliding mode control is implemented in order to make the movement of training and elevation can be controlled for having the desired angle position in the disturbance of pitch and roll. This paper is based on the study to compare the performance of neural network control and sliding mode control on the moving platform.

Index Terms—Cannon barrel, elevation and training, neural network control, pitch and roll, sliding mode control.

Wiwik Wiharti is with the Department of Electronics Engineering, State Polytechnic of Padang, Indonesia (e-mail: wiwik@polinpdg.ac.id).
Santi Anggraini is with the Department of Electronics Engineering, Electronic Engineering Polytechnic Institute of Surabaya, Indonesia (e-mail: santi@pens.ac.id). Ihsan Lumasa Rimra is with the Department of Telecommunication Engineering, State Polytechnic of Padang, Indonesia (e-mail: rimra@polinpdg.ac.id).

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Cite:Wiwik Wiharti, Santi Anggraini, and Ihsan Lumasa Rimra, "The Performance of Controlling Cannon Barrel Position on the Moving Platform Using Neural Network Control and Sliding Mode Control," International Journal of Computer Theory and Engineering vol. 7, no. 6, pp. 476-481, 2015.

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