LAUSR

Target tracking is one of the most widely used applications of UAVs and visual based tracking is the main method for non-cooperative tracking. In non-cooperative tracking missions, the UAV circles around the target and the gimbal rotates to keep the optic axis of the onboard camera pointing to the target. Compared with the biaxial gimbal, the single-axis gimbal system consists of only one torque motor, forming a great lightweight sensor suite, which also increases the requirement of the control accuracy. In the process of tracking moving target using a UAV with single-axis gimbal, there are still several challenges: (1) The completion of high precision and reliability of moving target tracking using UAV with only single-axis gimbal. (2) The non-linearity and uncertainty in the UAV system, where the non-linearity exists in the control of altitude, heading angle and roll angle. (3) The uncertainty in the expected turning radius of trajectory of the UAV when tracking a moving target without knowing its motion state. This paper proposes a vision-based fuzzy controller for a target tracking system consists of a fixed-wing UAV with single-axis gimbal. In this research, the innovations are described as follows: (1) A control algorithm is proposed for visual target tracking system consists of fixed-wing UAV with single-axis gimbal, which is able to guide the UAV to complete tracking task precisely and reliably. (2) Generation of roll command and heading command is immediately based on the information obtained from the images, skipping the step of calculating the velocity and position of the target, which can avoid unnecessary errors. (3) To deal with the non-linearities and uncertainties in the tracking system, seven fuzzy controllers are used to keep UAV circling around the target stably. (4) Flight tests are accomplished to verify the algorithm. Simulation results show that the maximum angle offset of the camera’s optic axis is 0.04°, and the angle offsets can be kept in the range of 5° in the further flight test, which shows that the algorithm is able to accomplish the task of tracking a moving target successfully.