Sampled-data robust visual servoing control for moving target tracking of an inertially stabilized platform with a measurement delay

The vision based moving target tracking is a key technology for unmanned systems in complex environments, which is mainly limited by the visual measurement delay and kinematic uncertainties. In this paper, a time-delay disturbance observer based sampled-data control approach is developed for the visual servoing of an inertially stabilized platform. As a camera is employed to capture the position of the target, the measurement delay is generated by the acquisition and the processing of the image information. Besides, kinematic uncertainties arising from the variable feature depth and inner-loop tracking errors of given reference signals are also unavoidable. To this end, the model of the perturbed and delayed system is established firstly. Due to the measurement delay, it is quite difficult to get the current system state. As such, a new time-delay disturbance observer is developed to estimate the previous disturbance and its differences, which facilitates predictions of the current state and the current disturbance. Based on above predictions, a sampled-data robust controller is designed with the rigorous stability analysis of the closed-loop system. Experiments on tracking a target are performed to validate promising qualities of the proposed method.