Simulation analysis on the application of neural network method to predict turret gun control parameters

Arif Wahjudi*, Deris Triana Noor

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In general, the parameters of a controller are determined based on the completion of the dynamic equations of the controlled system. However, dynamic equations for a complex system are usually hard to be solved, so that approach or simplification is necessary conducted. On the other hand, these approach and simplification will take away the true control parameter values. Therefore, neural network method is proposed in this study to determine the control parameters without going through the solution of the gun turret dynamic equation as a complex system. Optimal proportional and integral control parameters are predicted using the neural network method, then applied to the proportional-integral (PI) controller for the gun turret system that the turret angles lead to the desired angle. Based on numerical simulation results, gun turret performed by applying this method has a maximum overshoot percentage of 15.63% and maximum settling time of 12.14 seconds.

Original languageEnglish
Title of host publicationDisruptive Innovation in Mechanical Engineering for Industry Competitiveness
Subtitle of host publicationProceedings of the 3rd International Conference on Mechanical Engineering, ICOME 2017
EditorsVivien S. Djanali, Suwarno, Bambang Pramujati, Volodymyr A. Yartys
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735416994
DOIs
Publication statusPublished - 13 Jul 2018
Event3rd International Conference on Mechanical Engineering, ICOME 2017 - Surabaya, Indonesia
Duration: 5 Oct 20176 Oct 2017

Publication series

NameAIP Conference Proceedings
Volume1983
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference3rd International Conference on Mechanical Engineering, ICOME 2017
Country/TerritoryIndonesia
CitySurabaya
Period5/10/176/10/17

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