Optimized Neural Network-Direct Inverse Control for Attitude Control of Heavy-Lift Hexacopter

Authors

  • Bhakti Yudho Suprapto Department of Electrical Engineering, Universitas Indonesia, Kampus Baru UI Depok, Indonesia. Department of Electrical Engineering, Universitas Sriwijaya, Inderalaya, Sumatera Selatan, Indonesia.
  • Benyamin Kusumoputro Department of Electrical Engineering, Universitas Indonesia, Kampus Baru UI Depok, Indonesia.

Keywords:

DIC, Heavy-Lift Hexacopter, Neural Network, Optimized DIC,

Abstract

This paper discusses a neural network based on direct inverse control (DIC) to control the roll, pitch, and yaw in maintaining the hovering condition of a heavy-lift hexacopter. To improve the control of the hexacopter, the authors propose a DIC-optimized method of retraining the inverse model using new data collected from optimal motions of the hexacopter generated by the desired input. The experiment showed that both the DIC model and the DIC-optimized model had good performances with small MSSE values; however, the latter was more effective than the former.

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Published

2017-06-01

How to Cite

Suprapto, B. Y., & Kusumoputro, B. (2017). Optimized Neural Network-Direct Inverse Control for Attitude Control of Heavy-Lift Hexacopter. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(2-5), 103–107. Retrieved from https://jtec.utem.edu.my/jtec/article/view/2407

Issue

Vol. 9 No. 2-5: Circuit and System Advancement in Modern World IV

Section

Articles

License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)