Attitude Control of Stabilized Platform Based on Deep Deterministic Policy Gradient with Disturbance Observer

Abstract

A rotary steerable drilling system is an advanced drilling technology, with stabilized platform tool face attitude control being a critical component. Due to a multitude of downhole interference factors, coupled with nonlinearities and uncertainties, challenges arise in model establishment and attitude control. Furthermore, considering that stabilized platform tool face attitude determines the drilling direction of the entire drill bit, the effectiveness of tool face attitude control and nonlinear disturbances, such as friction interference, will directly impact the precision and success of drilling tool guidance. In this study, a mathematical model and a friction model of the stabilized platform are established, and a Disturbance-Observer-Based Deep Deterministic Policy Gradient (DDPG_DOB) control algorithm is proposed to address the friction nonlinearity problem existing in the rotary steering drilling stabilized platform. The numerical simulation results illustrate that the stabilized platform attitude control system based on DDPG_DOB can effectively suppress friction interference, improve non-linear hysteresis, and demonstrate strong anti-interference capability and good robustness.