Stabilizing a Nonlinear Helicopter Model: Advanced Hybrid Optimization Technique for Controlled Rotor Dynamics and Vibration Minimization Under External Disturbances.

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. [ABSTRACT FROM AUTHOR]