Modeling and control of a twin rotor mimo helicopter system using various control theories

Helicopters are used widely in transportation sector and in emergency cases due to the capability of quick taking off and landing on from different kinds of limited terrains and areas. The helicopter's control performance is related directly to the regulation and control of its two angles of rotation (pitch and yaw). Any changes of the helicopter's motion in pitch angle (angle of attack) leads to undesired changes in yaw angle, and simultaneously another changes in yaw angle that effects the pitch angle. A flight helicopter simulator with Two-degrees-of-freedom (2-dof) so-called TRMS (Twin Rotor Multi Input Multi Output System) is largely used in control labs as test platforms due to its comportment similarities with real helicopters whether in its high nonlinearity, or the important cross-coupling between its axial motions, or even in its instability under both closed-loop and open-loop. Therefore TRMS allows us effectively to investigate and design the desired controllers those can handle safely the challenging dynamics encountered in helicopter's control, through a system more simplified, and with the aid of its hardware structure assistance that provide a rapid prototyping environment for testing the designed control approaches. The control of TRMS is doable through the adjustment of the rotation speed of the two electrical motors. The present thesis presents an introduction, including a Newtonian modeling approach, to the used TRMS, then a synthesis and application of various control strategies those are already demonstrated by utilizing this test developed model with detailed design procedures in order to stabilize the TRMS. The first applied control approach is the classical PID control. Second control scheme is fuzzy control which has a linguistic structure and finally fuzzy type-2 Control algorithm is applied to a TRMS process to check the performance. The results are compared with classical PID controller and fuzzy logic. Time domain analysis and tabletted results show that better performance specification are obtained using type2 fuzzy control.