Hybrid Meta-Heuristic Optimization Algorithms with Integral Sliding Mode Control: Applied to Control Permanent Magnet Synchronous Generator-Based Wind Energy System
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Date
2026-05-15
Journal Title
Journal ISSN
Volume Title
Publisher
Mathematical Modelling of Engineering Problems Vol. 13, No. 4, April, 2026, pp. 663-683
Abstract
This study presents a comparative analysis of the performance of standard metaheuristic
algorithms and their hybrid variants for tuning the parameters of an Integral Sliding
Mode Controller (ISMC) applied to a Permanent Magnet Synchronous Generator
(PMSG) in wind energy conversion systems. Specifically, the Particle Swarm
Optimization (PSO) and Grey Wolf Optimizer (GWO) are investigated, along with two
hybrid strategies: PSO combined with the MATLAB-based nonlinear constrained
solver fmincon, and a PSO–GWO hybrid approach. These optimization techniques are
employed to improve the dynamic performance and robustness of the ISMC under
varying wind conditions. The optimized controllers are benchmarked against the
conventional Integral Sliding Mode–Field-Oriented Control (ISM–FOC) scheme. All
simulations are conducted in the MATLAB/Simulink environment. Results show that
the conventionally tuned ISMC exhibits a slower response and higher current-tracking
errors, with the quadrature current error reaching approximately 0.2 and the direct
current oscillating around 5 × 10⁻⁶ A, with a response time of 4.5 × 10⁻³ s. The results
clearly demonstrate that the proposed optimization approaches significantly enhance
control accuracy, reduce tracking errors, and mitigate chattering effects.