Automatic control of the microaerial vehicles’ attitude and position

The paper focuses on two automatic systems for the attitude and position’s control of the microaerial vehicles—insect type by using a nonlinear dynamic model, which describes the motion of microaerial vehicles with respect to the Earth tied frame. The attitude control is adaptive type, with the estimation of the inertia moments’ matrix and of the dynamic damping coefficients’ matrix in two variants: by means of the attitude vector or by using the quaternion vector. The new resulting control architectures use a vector for the control of the microaerial vehicles’ attitude, a proportional-derivative linear dynamic compensator, an error vector (whose elements are the estimated deviations of the inertia moments and dynamic damping coefficients with respect to the real ones), and the Lyapunov theory. In the two variants of the adaptive control, the control law is represented by the command aerodynamic moments and the wing rotation’s command vector, respectively; the control law for the microaerial vehicle position’s control is deduced in the same way. The two obtained control systems are validated by complex numerical simulations.

Optical Flow Sensor/INS/Magnetometer Integrated Navigation System for MAV in GPS-Denied Environment

The drift of inertial navigation system (INS) will lead to large navigation error when a low-cost INS is used in microaerial vehicles (MAV). To overcome the above problem, an INS/optical flow/magnetometer integrated navigation scheme is proposed for GPS-denied environment in this paper. The scheme, which is based on extended Kalman filter, combines INS and optical flow information to estimate the velocity and position of MAV. The gyro, accelerator, and magnetometer information are fused together to estimate the MAV attitude when the MAV is at static state or uniformly moving state; and the gyro only is used to estimate the MAV attitude when the MAV is accelerating or decelerating. The MAV flight data is used to verify the proposed integrated navigation scheme, and the verification results show that the proposed scheme can effectively reduce the errors of navigation parameters and improve navigation precision.