Optimal gain tuning of PI speed controller in induction motor drives using particle swarm optimization

Abstract

This article presents particle swarm optimization (PSO)-based optimal gain tuning of proportional integral (PI) speed controller in an induction motor (IM) drive (30 hp) with mine hoist load diagram. Optimization considers the load and speed variations, and provides appropriate gains to the speed controller to obtain good dynamic performance of the motor. IM performance is checked with the optimal gains through the simulation studies in MATLAB/SIMULINK environment. Results are compared with hand tuning (fixed gains) and fuzzy logic (FL) speed controller. Hybrid of FL and PSO-based PI controller for the speed control of given motor is also performed to eliminate the drawbacks of PI controller (overshoot and undershoot) and FL controller (steady-state error). From the simulation studies, hybrid controller produces better performance in terms of rise time, overshoot and settling time.

Adaptive control schemes for improving dynamic performance of efficiency-optimized induction motor drives

“…The offline Particle Swarm Optimization (PSO) algorithm is used to calculate the optimal value of flux and is stored in look-up table. The same algorithm is also used in [35] to calculate optimal PI gains for various operating regions of mine-hoist load and stored in look-up table. The different scalar and vector type energy optimal controllers are discussed in [6,31].…”

THD and Compensation Time Analysis of Three-Phase Shunt Active Power Filter Using Adaptive Spider Net Search Algorithm (ASNS)

“…By the appliance of shunt active power filters within the system can eliminate harmonic, reactive and unbalanced current still as improve the ability provide performance and so the steadiness of system. Today, the soft computing techniques are used wide for optimization of the system applied or in control system; algorithms [4]- [8] used for locating the optimized values of the controllers variables [4]- [12], optimization of active power filter using GA [9]- [12], power loss diminution using particle swarm optimization [13], neural network ANN Control [14]- [18] applied in each machinery and filter devices.…”

Soft Computing Techniques Applications and their Comparisons with Traditional pq Theory Based Control Schemes for Filter in Aircraft System

“…Today, the soft computing techniques like Fuzzy algorithms, ATS algorithms, Genetic Algorithm [4][5][6][7][8][9][10][11][12], particle swarm optimization [13], ANN [14][15][16][17][18] applied in every machinery and filter devices for optimization of the system applied or in the various control system.…”