Image Based Visual Servo Control with a Two-Axis Inertially Stabilized Platform Using Deep Deterministic Policy Gradient

This paper introduces a visual tracking control scheme for the two axes Inertially Stabilized Platform. An adaptive PID controller based on the Deep Deterministic Policy Gradient (DDPG) algorithm is used where it is treated as a Reinforcement Learning Policy. The optimal PID parameters are obtained at each time step via a training process. To effectively train the parameters, we address the problem of handling time delay and uncertainty of the system by presenting an observer system. Simulation results show that our method achieves good performance for various cases of time delay.