Adaptive sliding mode-based feedback linearization control for floating offshore wind turbine in region II DOI
Hao Chen,

Junjie Niu,

Youming Cai

et al.

International Journal of Green Energy, Journal Year: 2024, Volume and Issue: 22(2), P. 467 - 486

Published: Nov. 29, 2024

Wind turbine systems are highly nonlinear and time-variable. Under external interference, the normal stable operation of system is seriously affected. In addition, inertia wind causes a serious lag in speed tracking. These effects even more severe for floating offshore turbines (FOWT). To solve these problems, this paper proposes new optimal torque control form, further improves optimizes it. Firstly, feedback linearization used to eliminate part time-varying parameters, form obtained. Then, adaptive sliding mode optimize controller enhance robustness system. Finally, mode-based linearized (ASMFLOTC) was ASMFLOTC applied FOWT verify effectiveness its maximum power point tracking (MPPT) control. The results show that can better track reference speed, effectively reduce relative error, improve utilization rate energy. And from results, platform motion proposed not significantly different other controllers. does exacerbate while increasing output power. This shows feasibility.

Language: Английский

Design of advanced intrusion detection in cybersecurity using ensemble of deep learning models with an improved beluga whale optimization algorithm DOI
Fatimah Alhayan,

Nuha Alruwais,

Mohammad Alamgeer

et al.

Alexandria Engineering Journal, Journal Year: 2025, Volume and Issue: 121, P. 90 - 102

Published: Feb. 26, 2025

Language: Английский

Citations

0
Federated learning with Blockchain on Denial-of-Service attacks detection and classification of edge IIoT networks using Deep Transfer Learning model DOI
Monir Abdullah, Hanan Abdullah Mengash, Mohammed Maray

et al.

Computers & Electrical Engineering, Journal Year: 2025, Volume and Issue: 124, P. 110319 - 110319

Published: April 18, 2025

Language: Английский

Citations

0
Weighted Self-Paced Learning with Belief Functions DOI
Shixing Zhang, Deqiang Han, Jean Dezert

et al.

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: 255, P. 124535 - 124535

Published: Dec. 1, 2024

Language: Английский

Citations

2
Explainable artificial intelligence in web phishing classification on secure IoT with cloud-based cyber-physical systems DOI Creative Commons
Sultan Alotaibi, Hend Khalid Alkahtani, Mohammed Aljebreen

et al.

Alexandria Engineering Journal, Journal Year: 2024, Volume and Issue: 110, P. 490 - 505

Published: Oct. 15, 2024

Language: Английский

Citations

1
Adaptive sliding mode-based feedback linearization control for floating offshore wind turbine in region II DOI
Hao Chen,

Junjie Niu,

Youming Cai

et al.

International Journal of Green Energy, Journal Year: 2024, Volume and Issue: 22(2), P. 467 - 486

Published: Nov. 29, 2024

Wind turbine systems are highly nonlinear and time-variable. Under external interference, the normal stable operation of system is seriously affected. In addition, inertia wind causes a serious lag in speed tracking. These effects even more severe for floating offshore turbines (FOWT). To solve these problems, this paper proposes new optimal torque control form, further improves optimizes it. Firstly, feedback linearization used to eliminate part time-varying parameters, form obtained. Then, adaptive sliding mode optimize controller enhance robustness system. Finally, mode-based linearized (ASMFLOTC) was ASMFLOTC applied FOWT verify effectiveness its maximum power point tracking (MPPT) control. The results show that can better track reference speed, effectively reduce relative error, improve utilization rate energy. And from results, platform motion proposed not significantly different other controllers. does exacerbate while increasing output power. This shows feasibility.

Language: Английский

Citations

0