A Model Predictive Based Controller Design for a Class of Aerial Vehicle’s Trajectory Tracking Problem; In The Presence of Calculation’s Restrictive Assumptions

In the present paper, a class of dynamical systems for unmanned aerial vehicles (UAV) is illustrated and the position and attitude tracking control problem are proposed for the noted dynamics system. Nevertheless, the UAV dynamics system is considered as an underactuated system since the number of control command signals are lower than the outputs of the system. Consequently, the noted issue is the main challenge in the aforementioned control configuration. As a regard, a predictive-based, optimal controller is proposed for the system and the linear model predictive control architecture is examined in order to overcome the problem’s challenge due to the under actuation of the system and to achieve the tracking performance in an acceptable manner. Moreover, the UAV dynamics system is considered as a highly coupled and generally unstable system. in this regard, the control architecture should stabilize the open-loop dynamics system, satisfactorily. At last, the computational complexity of the online, optimal MPC controller is considered an important factor in practical and experimental issues. Thus, a computational complexity criterion is proposed for the control architecture in this paper, based on the number of iterations of the optimization algorithm in each time step. Conclusively, the controller performance and UAV dynamics system are examined in the simulation environment and the advantages and the capability of the controller and closed-loop system is illustrated by numerical results.

Keywords:

Unmanned Aerial Vehicle (UAV) , Underactuated Dynamics System , Model Predictive Control (MPC) , Online Controller , Iterative Optimization