Fractional-Order Predictive Functional Control of Industrial Processes with Partial Actuator Failures

Table 4

Related adjustable parameters used in three different evolutionary algorithms and corresponding optimal parameters in FOPFC.

Algorithm	Related adjustable parameters	Number of adjustable parameters	Optimal parameters in FOPFC
GA-FOPFC	Population size NP = 30, maximum number of iterations Imax = 50, crossover probability pc = 0.8, mutation parameter b = 3	4	P = 4, γ = 2.3549, λ = 0.8650
PSO-FOPFC	Swarm size NP = 30, maximum number of iterations Imax = 50, acceleration factors c1 = 1.49, c2 = 1.49, limits of velocity Vmax = 2, Vmin = −2	6	P = 3, γ = 0.8009, λ = 1.000
PEO-FOPFC	Population size NP = 10, maximum number of iterations Imax = 50, parameter b = 3 used in MNUM operation	3	P = 2, γ = 0.5659, λ = 0.831