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InECCE2019 pp 167-178 | Cite as

Elimination-Dispersal Sine Cosine Algorithm for a Dynamic Modelling of a Twin Rotor System

  • Shuhairie Mohammad
  • Mohd Falfazli Mat Jusof
  • Nurul Amira Mhd Rizal
  • Ahmad Azwan Abd Razak
  • Ahmad Nor Kasruddin NasirEmail author
  • Raja Mohd Taufika Raja Ismail
  • Mohd Ashraf Ahmad
Conference paper
  • 26 Downloads
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 632)

Abstract

This paper presents an improved version of Sine Cosine Algorithm (SCA). The original SCA is a simple algorithm and it offers a good accuracy. However, for some problems and fitness landscapes, the accuracy achievement of the algorithm is not at optimal. Search agents of the algorithm stuck at the local optima. The proposed new algorithm which is called an Elimination-Dispersal Sine-Cosine Algorithm adopts Elimination-Dispersal (ED) strategy from Bacterial Foraging Algorithm. The ED helps search agents to solve the local optima problem. At the same time, an elitism approach is applied in the proposed algorithm. The elitism ensures some agents continue the next search operation from the currently best found solution. The proposed algorithm is tested on CEC2014 benchmark functions that have various fitness landscapes and properties. The accuracy performance is compared with the original SCA and analyzed. It also is applied to acquire and optimize a dynamic model for a Twin Rotor System (TRS). Result of the modelling shows that the proposed algorithm achieves a better accuracy and thus present less modelling error and better dynamic response for the TRS.

Keywords

Elimination-dispersal Sine cosine algorithm Twin rotor system Dynamic modelling System identification 

Notes

Acknowledgements

This research is financially supported by the Fundamental Research Grant Scheme (FRGS/1/2016/ICT02/UMP/02/1) with the RDU number RDU160103. It is awarded by the Ministry of Higher Education Malaysia (MOHE) through Research and Innovation Department, Universiti Malaysia Pahang (UMP) Malaysia.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Shuhairie Mohammad
    • 1
  • Mohd Falfazli Mat Jusof
    • 1
  • Nurul Amira Mhd Rizal
    • 1
  • Ahmad Azwan Abd Razak
    • 1
  • Ahmad Nor Kasruddin Nasir
    • 1
    Email author
  • Raja Mohd Taufika Raja Ismail
    • 1
  • Mohd Ashraf Ahmad
    • 1
  1. 1.Faculty of Electrical & Electronics EngineeringUniversiti Malaysia PahangPekanMalaysia

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