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The purpose of this paper is to develop a nonlinear control system for flight trajectory control of flapping Micro Aerial Vehicles (MAVs), subjected to wind.

In the dynamic study and fabrication of the MAV, biomimetic principles are considered as the best inspiration for the MAV's flight as well as design constraints. The blade element theory, which is a two‐dimensional quasi‐steady state method, is modified to consider the effect of MAV's translational and rotational velocity. A quaternion‐based dynamic wrench method is then developed for the dynamic system.

The flapping flight dynamics is highly nonlinear and the system is under‐actuated, so any linear control strategy fails to meet any desired maneuver for trajectory tracking. In this study, a controller with quaternion‐based feedback linearization method is designed for the dynamical averaged system. It is shown that the original system is bonded to a stable limit cycle with desired amplitude and the controller inputs are bounded.

The effectiveness of a synthesized controller is proved for the cruse and the Cuban‐8 maneuver.

The authors' major contribution is developing feedback linearization quaternion‐based controller and deriving some essential mathematics for implementing quaternion model in the synthesis of controller. A piezoelectric‐actuated wing model is developed for the control system. Results of cursing and turning modes of the flight indicate the stability of the flight. Finally, an appropriate controller is designed for the Cuban‐8 maneuver so that the MAV would follow the trajectory with a bounded fluctuation.

The purpose of this paper is to propose an efficient and straightforward approach for system identification of a rotating single link flexible manipulator (RSLFM). Also, the achieved results are experimentally validated through identification procedure.

The proposed system identification approach is applied to a RSLFM with a tip mass. At first, the dynamic model of the system is derived using Lagrange method. Then, an efficient method is developed for identification of such a system. This method facilitates the nonlinear complicated identification problem of the RSLFM to a simplified root finding problem.

The main advantage of the developed method is to convert a complicated system identification process to a simple nonlinear equation solution. This approach uses small-size input/output data set and requires a short-time interval of data acquisition, which gives important advantages in lower computational load and lower execution time. The investigated approach is studied on experimental system identification of a single link flexible manipulator. To demonstrate this fact, the developed method is successfully applied in identification of two other mechanical systems; the inverted pendulum on a cart and the ball and beam apparatus.

In this work, the proposed identification approach has been originally applied to a RSLFM and two other mechanical examples. All obtained identification results show the performance and applicability of the developed method clearly. This approach is not restricted in using state space or transfer function. It has significant superiority in comparison with other known approaches including autoregressive with exogenous input (ARX) and Box-Jenkins (BJ).