Model predictive control of three-axis gimbal system mounted on UAV for real-time target tracking under external disturbances

The fact that Unmanned Aerial Vehicles (UAVs) move in a specific path and that the camera in the gimbal system mounted on the UAV adhere to the right target attracts the attention of many researchers. The effective control of the gimbal system directly affects the performance of the UAV which is tracking a predetermined moving target, following a specified path. The contribution of this study is not only modelling three-axis gimbal system mounted on mobile platform based on nonlinear Hammerstein block structure to control effectively using model predictive controller (MPC) but also improving real time target tracking performance under external disturbances. A novel Hammerstein model based MPC controller is successfully proposed for real time target tracking of three-axis gimbal system applying flight scenarios of UAV to be robust under external disturbances. In this study, firstly, the mathematical model of three-axis gimbal system mounted on UAV is developed based on traditional Newton-Euler method. Secondly, linear and nonlinear modeling based on the input and output data of the three-axis gimbal system mounted on UAV moving autonomously for target tracking is emphasized. The linear output error (OE) and nonlinear block structure Hammerstein models of the three-axis gimbal system are identified under the external disturbance effect, respectively. Then, the identified Hammerstein model is embedded in the flight control card, which included the three-axis gimbal system control to realize real time target tracking of the UAV. Afterwards, the MPC of three-axis gimbal system is realized under the external disturbance with linear and nonlinear models. Also, the performance of proposed MPC controller with Hammerstein model is evaluated comparing with conventional PID controller in terms of robustness and quantitative study of error analysis. Finally, the stability and robustness of the three-axis gimbal system controlled with the MPC algorithm has been investigated by the test results carried out in different scenarios. The simulation and experimental results show that the proposed MPC algorithm with Hammerstein model in this paper can ensure that the UAV exactly tracking the target while maintaining stability, even with (C) 2019 Elsevier Ltd. All rights reserved.