Optimal active disturbance rejection control with applications in electric vehicles

Dublin Core

Title

Optimal active disturbance rejection control with applications in electric vehicles

Subject

Active disturbance rejection control
Induction motor
Metaheuristics
Nonlinear control
Optimization

Description

This work proposes an optimal control strategy based on a modified active disturbance rejection control (ADRC) that considers disturbance weighting for a three-phase induction motor under rotor field-oriented control (FOC) to enhance energy efficiency. Induction motors (IMs) are widely used in electric vehicles (EVs) due to their cost-effectiveness and technological maturity. However, improving energy efficiency remains a key challenge, as it directly impacts vehicle range. The proposed approach employs ADRC, where part of the disturbance rejection task is handled offline by a hybrid optimization algorithm combining particle swarm optimization (PSO), tabu search (TS), and simulated annealing (SA) to tune a state-feedback controller. The controller parameters are optimized using a composite cost function that balances energy consumption and performance. Simulation and experimental results indicate that disturbance weighting has a significant impact on both problem complexity and performance. Optimal weighting improves the overall system response compared to conventional disturbance rejection methods. Energy and performance analyses show that disturbance weighting enhances energy usage compared to the traditional ADRC method, suggesting a novel efficiency control strategy for electric machines.

Creator

Juan Quecan-Herrera1, Sergio Rivera1, Jorge Neira-García2, John Cortés-Romero1

Source

Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA

Date

Sep 10, 2025

Contributor

PERI IRAWAN

Format

PDF

Language

ENGLISH

Type

TEXT

Files

Collection

Citation

Juan Quecan-Herrera1, Sergio Rivera1, Jorge Neira-García2, John Cortés-Romero1, “Optimal active disturbance rejection control with applications in electric vehicles,” Repository Horizon University Indonesia, accessed January 12, 2026, https://repository.horizon.ac.id/items/show/10325.