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.
Highlights
The widespread of high-performance variable speed drive systems in modern industrial applications imposes a necessity to develop the control circuits of these systems in order to follow drive commands quickly and accurately in accordance with load requirements
Due to the fact that VSD systems have a significant impact on the power quality, it is important to improve the efficiency of control circuits in these systems [1]
This paper introduces a new technology to adjust both PI and PIDN parameters used to generate control signals needed to drive the fourquadrant chopper transistors in the studied system by comparing between Grey wolf optimization (GWO) & Particle Swarm Optimization (PSO) algorithms
Summary
The widespread of high-performance variable speed drive systems in modern industrial applications imposes a necessity to develop the control circuits of these systems in order to follow drive commands quickly and accurately in accordance with load requirements. The switches of the inverter have been controlled using the SPWM modulation technique and results showed that the suggested controller has achieved an adequate speed regulation at high mechanical load changes, it gave small steady error and the controller has been found to be unstable at extremely low speed or high-speed change Optimization algorithms such as particle swarm optimization algorithm PSO, genetic algorithm GA, and others have demonstrated high efficiency and good results by improving steady state characteristics [9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20].
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