Real-time parameter identification for highly coupled nonlinear systems using adaptive particle swarm optimization

  • B. Ranjbar Sahraei Kauno technologijos universitetas
  • A. Nemati
  • A. A. Safavi

Abstract

The In this paper, an Adaptive Particle Swarm Optimization (APSO) method is proposed for parameter identification of highly coupled electromechanical sys-tems. Using some modifications on the APSO, better com-putational efficiency is achieved. In this way, the speed of real-time identification procedure is improved. In addition, to show the effectiveness of the proposed method, it is im-plemented on a real ball on plate setup and its dynamic model is achieved. Both the simulation and the experimen-tal results show that parameter identification of the pro-posed algorithm is significantly improved when compared with other existing identification methods based on the traditional PSO and Genetic Algorithm (GA).
Published
2016-08-10
Section
Articles