Grey Wolf Optimization Based Integral-Backstepping Controller For An Unmanned Aerial Vehicle

Abstract

The Quadcopter Is A Small Rotary-Wing Unmanned Aerial Vehicle Made Up Of Four Identical Motors With End-Fixed Individual Propellers. It Is Highly Nonlinear, Strongly Coupled, And Affected By Wind, And Parameter Uncertainty Makes It Unstable. Due To The High Input-Output Interaction, Designing A Robust And Effective Control Mechanism To Handle Parameter Uncertainty Is The Most Challenging. In This Thesis, Grey Wolf Optimization And The Integral-Based Nonlinear Backstepping Control (GWO-IBS) Method Are Designed To Improve The Problems. The Nonlinear Mathematical Model Of The Quadcopter Was Formulated By Using The Newton-Euler Mechanism. The Model Was Represented In A Nonlinear State Space Form Suitable To Drive The Integral Nonlinear Backstepping Control Law For All State Output. The Integral And Backstepping Gains Are Optimized Using The Grey Wolf Optimization Technique. The Overall System Analysis Is Performed Using MATLAB 2021a. Simulink And Helical Trajectory Are Also Designed For Trajectory Tracking Of The Horizontal Motion Of The System. The Performance Of The Robustness And Stability Of The Proposed Controller Was Tested By Applying A Wind Disturbance For 25 Seconds With Varying Magnitudes And Loads. The Result Shows That The Proposed Control Can Reject Disturbances And Handle Uncertainty. Finally, The Proposed Controller Is Compared With Integral-Based Backstepping (IBS) And Evaluated Their Degree Of Stability In Terms Of RMSE. From The Evaluation, The New Proposed GWO-IBS Gives Small RMSE And A Better Improvement Of 81.68% For X-Trajectory, 93.65% For Y-Trajectory, 99.86% For Altitude, And 48.38% For Roll Angle, 41.29% For Yaw Angle And 88.75% For Yaw Angle Than IBS. In Addition, It Shows Better Performance In Unknown Disturbance Rejection And Load Mass In All Scenarios.