Ant Colony Optimized Controller for Fast Direct Torque Control of Induction Motor

Author:

Albalawi Hani12,Zaid Sherif A.1ORCID,El-Shimy Mohmed E.1ORCID,Kassem Ahmed M.3

Affiliation:

1. Electrical Engineering Department, Faculty of Engineering, University of Tabuk, Tabuk 47913, Saudi Arabia

2. Renewable Energy & Energy Efficiency Centre (REEEC), University of Tabuk, Tabuk 47913, Saudi Arabia

3. Electrical Engineering Department, Faculty of Engineering, Sohag University, Sohag 82524, Egypt

Abstract

Induction motor (IM) drives have tremendous applications as high-performance drives in things such as mine winders, machine tools, electric vehicles, and elevators. Usually, IM drives controlled by direct torque control are preferred for these applications due to their fast torque control and simplicity compared with IM drives with field-oriented control. Proportional–integral–derivative (PID) controllers are commonly used to control IM drives using DTC. Though these controllers are simple and provide excellent response for linear systems with constant set points, they perform poorly with variable set points and IM motor parameter uncertainties. Hence, many control techniques and optimization algorithms have been applied to improve IM drive performance. This paper proposes an IM drive controlled using direct torque control principles, but with the power converter operation optimized to give fast torque performance. The IM drive speed response is improved using an optimized fuzzy PID (FPID). The FPID optimization is accomplished by the ant colony optimization (ACO) algorithm. All components of the IM drive with the optimized control system were simulated using the MATLAB/Simulink platform. The responses of the introduced drive using three different controllers—conventional PID, FPID, and optimized FPID—were compared. The simulation results indicate that the optimized FPID controller provided the best performance in terms of speed and torque. Additionally, the performance of the IM with the proposed optimized FPID under parameter uncertainties was studied. The simulation results indicated the robustness of the optimized FPID controller against parameter uncertainties.

Funder

University of Tabuk

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

Reference44 articles.

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