چكيده لاتين
When air vehicles are flying at a high altitude, their dynamic parameters can change. Air vehicles are very sensitive to flight conditions, physical parameters, and atmospheric disturbance. At this time, attitude control is very important. Attitude must be adjusted repeatedly during the flight. Due to the existence of uncertain flight parameters, noise of sensors, reduction of moment of inertia and mass during flight, air density changes, designing a suitable controller that has the ability to deal with external disturbances, changes dynamic of the model and physical parameter of the system, is one of the most basic parts in the field of flight control research.
In this thesis, an Active disturbance rejection control (ADRC) based on the super twisting algorithm for attitude control of 6 degree-of-freedom nonlinear air vehicle is proposed. In the first step, the non-linear air vehicle model is introduced and converted to coupled equations. Then, the non-linear extended state observer is applied to estimate system uncertainties and system disturbance. Super-twisting sliding mode controller is designed and ADRC methodology is applied based on it. The Tracking differentiator to reduce overshoot and speed of convergence is proposed. The performance is tested under the Dryden turbulence disturbance, noise of sensor and actuators disturbance. Stability of the ESO and ADRC are theoretically analyzed and Close loop stability is proved. Finally, the results are compared with the Super twisting algorithm-based controller and Linear Active Disturbance Rejection. Simulation results confirm high performance of the proposed ADRC for control the aircraft to track the desired path and states estimation under strong disturbances.
In last part, this control methodology is designed for the rigid spacecraft to perform attitude maneuvers. In the design and tuning of the controller, constraints on the reaction wheels torque and angular momentum are considered. the proposed controller is implemented on the spacecraft attitude control subsystem simulator to study the effectiveness of the controller in close-to-reality situations in the presence of uncertainties and internal/external disturbances.
