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. 2020 Nov 8;6(11):e05438.
doi: 10.1016/j.heliyon.2020.e05438. eCollection 2020 Nov.

Steady state analysis of modern industrial variable speed drive systems using controllers adjusted via grey wolf algorithm & particle swarm optimization

Affiliations

Steady state analysis of modern industrial variable speed drive systems using controllers adjusted via grey wolf algorithm & particle swarm optimization

Safwan Nadweh et al. Heliyon. .

Abstract

This paper presents the reconfiguration of control circuit designed to control four-quadrant chopper placed in the variable speed drive system (VSDS)'s DC-link. The purpose of this design is to reduce the overall total harmonic distortion THD% of input current, and the ripple factor (RF) of the DC-link current in this system. Both of Grey Wolf Algorithm (GWO) & Particle Swarm Optimization (PSO) have been used to get the optimal parameters of proportional integral PI and proportional integral differential with filter PIDN controllers. The variable speed drive system and the proposed filter have been modeled in integration with the suggested algorithms to determine the optimal values of the controllers' parameters. The grey wolf algorithm GWO outperformed the PSO algorithm in term of reaching the optimum parameters in less number of iterations in both dynamic and static work conditions. Also, the time response of the system with GWO is better than with PSO.

Keywords: Electrical engineering; Electrical system; Energy; Four quadrant chopper; Grey wolf optimization; Industrial engineering; Particle swarm optimization; Power quality; Variable speed drive system.

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Figures

Figure 1
Figure 1
Particle swarm optimization.
Figure 2
Figure 2
PSO algorithm: (a) Main steps of PSO, and (b) The general flowchart of PSO search algorithm.
Figure 3
Figure 3
Leadership hierarchy of grey wolves.
Figure 4
Figure 4
Hunting behavior by grey wolves (a) Tracking, approaching, observing prey, (b-c-d) Chasing prey, surrounding them and harassing them until they stop moving, (e) Attacking prey.
Figure 5
Figure 5
Two-dimensional location vectors and their possible upcoming locations.
Figure 6
Figure 6
Locations updates in GWO.
Figure 7
Figure 7
Attacking prey.
Figure 8
Figure 8
The flowchart of GWO algorithm.
Figure 9
Figure 9
Studied system.
Figure 10
Figure 10
Control plan used to generate the voltages biases necessary for transistors chopper operations of the studied drive system.
Figure 11
Figure 11
Detailed schematic diagram of the objective function.
Figure 12
Figure 12
The values of the objective function when using GWO and PSO algorithms.
Figure 13
Figure 13
System input currents when using both PSO and GWO for controllers' parameters tuning.
Figure 14
Figure 14
The total harmonic distortion factor of the studied system input current when using GWO.
Figure 15
Figure 15
Phase to phase input voltage using GWO and PSO.
Figure 16
Figure 16
Dc-link current of the studied system using GWO and PSO algorithms.
Figure 17
Figure 17
The voltage on chopper transistors in the DC-link of the studied system.

References

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