First application of symbiotic organisms search algorithm to off-line optimization of PI parameters for DSP-based DC motor drives


Celik E., ÖZTÜRK N.

NEURAL COMPUTING & APPLICATIONS, vol.30, no.5, pp.1689-1699, 2018 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 30 Issue: 5
  • Publication Date: 2018
  • Doi Number: 10.1007/s00521-017-3256-5
  • Title of Journal : NEURAL COMPUTING & APPLICATIONS
  • Page Numbers: pp.1689-1699

Abstract

To enhance the performance and dynamics of a direct current (DC) motor drive, this paper proposes a new alternative based on recently introduced powerful symbiotic organisms search (SOS) algorithm for tuning proportional integral parameters. While imitating the symbiotic behavior that is seen among organisms in an ecosystem, SOS has important features such that it does not require tuning parameters, and its implementation is very easy with efficient three phases. After obtaining the optimized values of K (p) - K (i) pair within the accurately prepared simulation software, they are used in real time. By managing the DC motor speed-controlled system with DSP of TMS320F28335, several simulations and experimental results confirming the performance of our proposal are presented along with comparisons against those of particle swarm optimization (PSO), genetic algorithm (GA), and Ziegler-Nichols (Z-N) tuning method. Results explicitly show that SOS is the pioneer in yielding better tracking performance and load disturbance rejection capability of the concerned drive system, which is followed by PSO, GA, and Z-N method, respectively. This has been achieved due to the fact that the gains obtained by SOS are more performant than those obtained by other applied methods.