TY - JOUR
T1 - Efficient design of wideband digital fractional order differentiators and integrators using multi-verse optimizer
AU - Ali, Talal Ahmed Ali
AU - Xiao, Zhu
AU - Mirjalili, Seyedali
AU - Havyarimana, Vincent
PY - 2020/8
Y1 - 2020/8
N2 - In this paper, a novel method is proposed based on combining L1-norm optimally criterion with a recently-proposed metaheuristic called multi-verse optimizer (MVO) to design 2nd–4th order stable, minimum phase and wideband infinite impulse response (IIR) digital fractional order differentiators (DFODs) for the fractional order differentiators (FODs) of one-half, one-third and one-fourth order. To confirm the superiority of the proposed approach, we conduct comparisons of the MVO-based designs with the real-coded genetic algorithm (RCGA) and particle swarm optimization (PSO)-based designs in terms of accuracy, robustness, consistency, and efficiency. The transfer functions of the proposed designs are inverted to obtain new models of digital fractional order integrators (DFOIs) of the same order. A comparative study of the frequency responses of the proposed digital fractional order differentiators and integrators with the ones of the existing models is then conducted. The results demonstrate that the proposed designs yield the optimal magnitude responses in terms of absolute magnitude error (AME) with flat response profiles.
AB - In this paper, a novel method is proposed based on combining L1-norm optimally criterion with a recently-proposed metaheuristic called multi-verse optimizer (MVO) to design 2nd–4th order stable, minimum phase and wideband infinite impulse response (IIR) digital fractional order differentiators (DFODs) for the fractional order differentiators (FODs) of one-half, one-third and one-fourth order. To confirm the superiority of the proposed approach, we conduct comparisons of the MVO-based designs with the real-coded genetic algorithm (RCGA) and particle swarm optimization (PSO)-based designs in terms of accuracy, robustness, consistency, and efficiency. The transfer functions of the proposed designs are inverted to obtain new models of digital fractional order integrators (DFOIs) of the same order. A comparative study of the frequency responses of the proposed digital fractional order differentiators and integrators with the ones of the existing models is then conducted. The results demonstrate that the proposed designs yield the optimal magnitude responses in terms of absolute magnitude error (AME) with flat response profiles.
KW - Digital fractional order differentiator
KW - Digital fractional order integrator
KW - Genetic Algorithm
KW - L-norm
KW - Metaheuristic
KW - Multi-verse optimizer
KW - Optimization
KW - Particle Swarm Optimization
UR - http://www.scopus.com/inward/record.url?scp=85084957645&partnerID=8YFLogxK
U2 - 10.1016/j.asoc.2020.106340
DO - 10.1016/j.asoc.2020.106340
M3 - Article
AN - SCOPUS:85084957645
SN - 1568-4946
VL - 93
JO - Applied Soft Computing
JF - Applied Soft Computing
M1 - 106340
ER -