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Hybrid Meta-Heuristic Optimization Algorithms with Integral Sliding Mode Control: Applied to Control Permanent Magnet Synchronous Generator-Based Wind Energy System
(Mathematical Modelling of Engineering Problems Vol. 13, No. 4, April, 2026, pp. 663-683, 2026-05-15) Arabi, Marwa; Zennir, Youcef; Bounezour, Hicham; Benghanem, Mohamed
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.
Multi-Objective TEO and GOA Optimization of PID Controllers Applied to an Altitude and Yaw Mission of Quadrotor UAV Swarm
(ALGERIAN JOURNAL OF SIGNALS AND SYSTEMS (AJSS).Vol. 11, Issue 1.p 51/p 58, 2026-03-01) Hermouche, Bilel; Zennir, Youcef
This paper produces a distributed control system to be used for collaborative UAV quadrotor
simultaneous hovering and yawing missions in a leader-follower architecture, PID control is used in the
altitude controller and the yaw controller for each single quadrotor with well-tuned parameters provided by two
multi-objective optimization algorithms MOTEO and MOGOA, in the simulation and discussion section we
show that due to the well system performances the produced parameters by MOTEO-PID combination are
chosen to be the gains of the altitude and yaw controllers of the distributed control system for the hovering and
yawing mission using a leader-follower architecture.
STPA-FTA hybrid hazard analysis framework applied to a high integrity pressure protection system
(Life Cycle Reliability and Safety Engineering.Springer Nature., 2026-03-26) Rehail, Yasser; Tchouar, Noureddine; Zennir, Youcef; Carniel, Andrei
The increasing complexity of petrochemical systems demands innovative hazard analysis methods capable of capturing
both component and systemic failures. In this paper, we propose a new hazard analysis framework that integrates SystemTheoretic Process Analysis (STPA) with traditional Fault Tree Analysis (FTA). Initially, STPA is applied to identify Unsafe
Control Actions (UCAs) and associated loss scenarios. Subsequently, FTA is employed to model dysfunctional component
behaviors and quantify critical risk metrics, including the Probability of Failure on Demand (PFDavg), Minimal Cut Sets
(MCSs), and Safety Integrity Level (SIL) using GRIF software. Finally, STPA outputs are incorporated into the traditional
FTA by treating UCAs as basic developed events. The framework is applied to a High Integrity Pressure Protection System (HIPPS 2351) safeguarding the C-63 distillation column at the Skikda RA1K refinery. The results revealed additional
MCSs that were not discovered by the traditional FTA, which increased the number of MCSs from 8 to 39. Furthermore,
the Birnbaum Importance Factor is applied to rank and prioritize UCAs, identifying the most critical UCAs (UCA 1
through UCA-15) that have a significant impact on the HIPPS 2351 reliability. Overall, the proposed framework provides
a comprehensive hazard analysis covering both qualitative and quantitative aspects.
Application of Systems-Theoretic Process Analysis and D-HiGraph Modeling for Risk Analysis in a Continuous Casting Machine
(International Journal of Safety and Security Engineering Vol. 16, No. 1, January, 2026, pp. 43-53, 2026-01-31) Larit, Khalid; Berri, Islam; Zennir, Youcef; Rodriguez, Manuel; Benghanem, Mohamed; Liu, Yiliu
Continuous casting machines (CCMs) play a crucial role in steel production, but their
complexity and high level of automation pose significant challenges to ensuring
operational safety. This study explores a combined approach using Systems-Theoretic
Process Analysis (STPA) and D-HiGraph modeling to identify and better understand
potential hazards in a CCM unit. STPA is used to define possible losses, hazards, and
unsafe control actions (UCAs) within the system. To support the analysis, a control
structure model is developed using D-HiGraph, which provides a clear, hierarchical view
of how controllers, sensors, actuators, and human operators interact. The results highlight
several critical UCAs, particularly in areas such as mold level regulation, adjustment of
withdrawal speed, and emergency shutdown procedures. By visualizing these
relationships with D-HiGraph, it becomes easier to trace the origin of unsafe scenarios
and gain deeper insight into system behavior. Overall, this integrated method offers a
structured and effective way to improve safety analysis in CCMs and contributes to more
robust design and operational strategies in steelmaking environments.
Sliding Mode Controller and Fuzzy PID for Doubly Fed Induction Generator
(Journal Européen des Systèmes Automatisés Vol. 59, No. 1, January, 2026, pp. 21-28, 2026-01-31) Chetioui, Lotfi; Achouri, Mourad; Zennir, Youcef; Benghanem, Mohamed
In modern control engineering, the demand for robust and adaptive control strategies is
critical for managing complex, nonlinear, and uncertain systems. This paper investigates
sliding mode control (SMC) and fuzzy PID control applied to a doubly fed induction
generator (DFIG), two advanced techniques widely used in both industrial and academic
contexts. SMC is known for its high robustness and finite-time convergence; however, it
suffers from chattering and dependence on accurate system modeling. In contrast, the
fuzzy PID controller combines the classical PID structure with fuzzy logic to provide
adaptive and smooth control without requiring a precise mathematical model. Through
theoretical analysis and a review of recent research findings, this study highlights the
strengths and limitations of each method in terms of robustness, adaptability,
implementation complexity, and application suitability. The results indicate that while
SMC excels in robustness and precision, the fuzzy PID controller offers a more flexible
and user-friendly alternative for systems with nonlinear or uncertain dynamics. Ultimately,
the choice between the proposed methods depends on the specific requirements of the
target application, with future research opportunities lying in hybrid strategies that
combine the robustness of SMC with the adaptability of fuzzy PID control to enhance
performance in renewable energy systems.