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Stabilizing a Nonlinear Helicopter Model: Advanced Hybrid Optimization Technique for Controlled Rotor Dynamics and Vibration Minimization Under External Disturbances
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Stabilizing a Nonlinear Helicopter Model: Advanced Hybrid Optimization Technique for Controlled Rotor Dynamics and Vibration Minimization Under External Disturbances
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Journal Article
Stabilizing a Nonlinear Helicopter Model: Advanced Hybrid Optimization Technique for Controlled Rotor Dynamics and Vibration Minimization Under External Disturbances
2025
Overview
Problem
Nonlinear vibrations in helicopter systems present considerable challenges to performance and stability.
Control Scheme
This paper presents a novel control framework tailored for a fuzzy-proportional-integral-derivative (FPID) controller, specifically focusing on nonlinear vibration management and helicopter rotor dynamics control. The constraints of controller are optimized using a hybrid Giza Pyramid Construction Teaching Learning Based Optimization algorithm. We utilize a nonlinear helicopter hardware model as a benchmark, subjecting it to external disturbances created by high-speed fans to replicate real-world scenarios.
Computation
By employing the MATLAB/Simulink platform, our computational technique effectively mitigates disturbances while minimizing critical fitness functions: Integral-Time-Square-Error (ITSE), Integral-Square-Error (ISE), and Integral-Absolute-Error (IAE).
Conclusion
The results demonstrate that our hybridized algorithm outperforms existing optimization techniques, showcasing improved stability and reliability in both simulations and real-time applications. This research significantly advances helicopter control methodologies and enhances the overall performance of helicopter systems under challenging conditions.
Publisher
Springer Nature Singapore,Springer Nature B.V
Subject
