ELM-based parallel compensation control for perturbed plants with hysteresis using robust right coprime factorization

In this paper, for compensating the effect of hysteretic nonlinearity which precedes perturbed plants, an Extreme Learning Machine (ELM) based parallel compensator is designed by using properties between play and stop hysteresis operators. Based on the compensated perturbed plants, operator-based feedback controllers and tracking controllers are designed to guarantee the output tracking performance by using robust right coprime factorization. Finally, the numerical simulation results are presented to validate the effectiveness of the proposed method.