Grey Wolf Optimizer in Design Process of the Recurrent Wavelet Neural Controller Applied for Two-Mass System

Abstract

In this paper, an adaptive speed controller of the electrical drive is presented. The main part of the control structure is based on the Recurrent Wavelet Neural Network (RWNN). The mechanical part of the plant is considered as an elastic connection of two DC machines. Oscillation damping and robustness against parameter changes are achieved using network parameters updates (online). Moreover, the various combinations of the feedbacks from the state variables are considered. The initial weights of the neural network and the additional gains are tuned using a modified version of the Grey Wolf Optimizer. Convergence of the calculation is forced using a new definition. For theoretical analysis, numerical tests are presented. Then, the RWNN is implemented in a dSPACE card. Finally, the simulation results are verified experimentally.

Skin cancer classification based on an optimized convolutional neural network and multicriteria decision-making

“…During this stage, a modification was performed to the classical GWO, particularly for coefficient a, as denoted by Equation 23, to increase the exploration time for finding more solutions in the search space [51]. This algorithm was termed GWO1, while the algorithm related to the classical GWO was termed GWO2.…”

“…In nature, wolves are hunting prey optimally. The algorithm applies this principle by organizing wolves' roles in the pack according to the hierarchy [50,51]. Based on the many roles that wolves play in the hunting process, the members of the pack in GWO are separated into four groups.…”

“…Based on the many roles that wolves play in the hunting process, the members of the pack in GWO are separated into four groups. The distinctive groups are alpha, beta, delta, and omega, with alpha denoting the greatest hunting solution [49][50][51]. The wolf's category beta assists in hunting decisions, while the third-class delta surrounds the first and second classes for scouting and hunting.…”

“…Thus, the roles of wolves in hunting prey can be identified as tracking, pursuing, and assaulting [49]. The mathematical modeling of the GWO according to the social behavior of the wolves is explained in the following steps [22,[49][50][51].…”

A novel hybrid cuckoo search algorithm for optimization of a line-start PM synchronous motor

“…In heuristic optimization algorithms, the optimal solution is sought within a group of individuals called, depending on the algorithm: a generation (genetic algorithms), a swarm [9,10] (swarm methods), a colony (bat algorithm), and even a pack [11,12] (grey wolf method). If considering successive iterations, the optimization procedure tries to find the optimal solution by moving a group of "agents" around the permissible area.…”