**4.1. The algorithm**

190 Induction Motors – Modelling and Control

According to (Brownlee, 2011):

The number of particles should be low, around 20-40

The learning factors (biases towards global and personal best positions) should be

A local bias (local neighborhood) factor can be introduced where neighbors are

 Particles may leave the boundary of the problem space and may be penalized, be reflected back into the domain or biased to return back toward a position in the

determined based on Euclidean distance between particle positions.

The speed a particle should be bounded.

between 0 and 4, typically 2.

Algorithm 1: Pseudocode for PSO (Brownlee, 2011).

The main steps in induction motor design optimization are shown in Fig. 6.
