Hybrid enhanced particle swarm optimization for VTOL UAV sliding mode controller: A methodological
This paper introduces an improved Sliding Mode Controller (SMC) using Hybrid Enhanced Particle Swarm Optimization (HEPSO) for parameter tuning, optimizing c1, c2, η1, and η2. HEPSO integrates adaptive inertia weights (AIW), unified factor enhancement (UFE), and global optimal particle training (GOPT), enhancing its performance. Validated against CEC2022 benchmark functions, HEPSO excels in convergence and precision over other PSO variants. Its practicality was tested in VTOL UAV simulations, outperforming PSO-SMC, IPSO-SMC, and UPS-SMC, proving its effectiveness in UAV control systems. This study upgrades SMC performance and offers a robust control strategy for UAVs.
Authors
- Tianyu Zhang (ORCID: https://orcid.org/0000-0001-5647-6014)
- He Wang (ORCID: https://orcid.org/0000-0002-0987-640X)
- Zhong Wei Liu
- S. Huang (ORCID: https://orcid.org/0000-0001-7461-0854)
Institutions
- University of Science and Technology Liaoning (CN)
Publication Details
- Journal
- Ain Shams Engineering Journal
- Published
- 2025-08-22
- DOI
- https://doi.org/10.1016/j.asej.2025.103694
- Citations
- 1
- Primary Topic
- Adaptive Control of Nonlinear Systems
- Type
- article
- Field-Weighted Citation Impact
- 1.21