Skip to main content
SpringerLink
Log in
Book cover

Innovations in Electronics and Communication Engineering pp 95–102Cite as

Controlling Power System of Earth Station Using Embedded System

  • Conference paper
  • First Online:

  • 917 Accesses

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 7))

Abstract

We have used two methods for earth station power controller is designed by Cortex M3 by using LPC 1768 board and FPGA board. Different loads having different power requirements and different fault conditions occurred. Earth station having 800 W inverter and having two failures named hard failure and soft failure. We have used solar energy as a main source of earth station and diesel generator for failure conditions. Using neural network, we developed algorithm in embedded C as per different types of failure, battery voltage, and solar voltage.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Himaya T, Kouzuma S, Lanakubo T, Orteyer TH (2015) Evaluation of neural network based real time maximum power tracking controller for PV system. IEEE Power Energy Soc

    Google Scholar 

  2. El-Madany HT, Fahmy FH, El-Rahman NMA, Dorrah HT (2014) Design of FPGA based neural network controller for earth station power system. TELKOMNIKA 10(2):281–290

    Article  Google Scholar 

  3. Petchjatuporn P, Ngamkham W, Khaehintung N (2005) A solar-powered battery charger with neural network maximum power point tracking implemented on a low-cost PIC-microcontroller. In: TENCON 2005, IEEE region 10 Nov 2005

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. VLSI and Embedded System, MIT College of Engineering, Pune, India

    Sunil V. Bagade

  2. ECE Department, MIT College of Engineering, Pune, India

    V. V. Shete

Authors
  1. Sunil V. Bagade
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. V. V. Shete
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sunil V. Bagade .

Editor information

Editors and Affiliations

  1. Guru Nanak Institutions, Ibrahimpatnam, Telangana, India

    H. S. Saini

  2. Guru Nanak Institutions, Ibrahimpatnam, Telangana, India

    R. K. Singh

  3. Guru Nanak Institutions, Ibrahimpatnam, Telangana, India

    K. Satish Reddy

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bagade, S.V., Shete, V.V. (2018). Controlling Power System of Earth Station Using Embedded System. In: Saini, H., Singh, R., Reddy, K. (eds) Innovations in Electronics and Communication Engineering . Lecture Notes in Networks and Systems, vol 7. Springer, Singapore. https://doi.org/10.1007/978-981-10-3812-9_10

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-3812-9_10

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3811-2

  • Online ISBN: 978-981-10-3812-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation