An improved chaos optimization algorithm-based parameter identification of synchronous generator

Parallel chaos optimization algorithm with migration and merging operation

“…There are totally five parameters to be extracted for this model: X = [R s ,R sh ,I ph ,I sd ,n] as in Eq. (6). Extracted optimal parameters values X * and the RMSE value by optimization algorithms for the PV module have been reported in Table 11.…”

“…Gauss map xn+1 = 0, xn = 0, xn+1 = 1 xn mod(1), xn / = 0 xn ∈ (0, 1) 5 ICMIC map xn+1 = sin(x n ) xn ∈ (−1, 1) ˛ = 2 6 Logistic map xn+1 = ϕxn(1 − xn) xn ∈ (0, 1) ϕ = 4 7…”

“…Generally speaking, chaos has several important dynamical characteristics, namely, the sensitive dependence on initial conditions, ergodicity, pseudo-randomness, and strange attractor with self-similar fractal pattern [1][2][3][4][5]. Recently, chaotic sequences generated by means of chaotic maps have been used in the development of global optimization techniques, and particularly, in the specification of chaos optimization algorithm (COA) [2][3][4][5][6][7][8][9]. Due to the unique characteristic of chaos, COA carries out global exploration search at higher speed than stochastic ergodic searches that depend on the probabilities [5][6][7][8][9].…”

“…Recently, chaotic sequences generated by means of chaotic maps have been used in the development of global optimization techniques, and particularly, in the specification of chaos optimization algorithm (COA) [2][3][4][5][6][7][8][9]. Due to the unique characteristic of chaos, COA carries out global exploration search at higher speed than stochastic ergodic searches that depend on the probabilities [5][6][7][8][9]. The main advantages of COA include: (a) COA escapes from local minima more easily than classical stochastic optimization algorithms such as genetic algorithm (GA), simulated annealing (SA) and some meta-heuristics algorithms including particle swarm optimization (PSO), ant colony optimization algorithm (ACO), differential evolution (DE), and so on [9]; (b) COA does not depend on the strict mathematical properties of Circle map xn+1 = xn + ϑ − ( 2 ) sin(2 xn)mod (1) xn ∈ (0, 1) ϑ = 2.5, = 5 3 Cubic map xn+1 = xn(1 − x 2 n ) xn ∈ (0, 1) = 2.59 4…”

Multiobjective Parallel Chaos Optimization Algorithm with Crossover and Merging Operation

“…Facing single objective optimization problems, a lot of existing algorithms, such as genetic algorithm (GA), simulated annealing (SA), particle swarm optimization (PSO), differential evolution (DE), harmony search algorithm (HSA), and compact pigeon-inspired optimization [16][17][18], have demonstrated excellent performance, but trapping in local optimum still remains a challenge. Chaos optimization algorithm (COA) is a recently developed global optimization technique based on chaos theory and particularly is the specification of the use of numerical chaotic sequences.…”