Sliding Mode Control with Nonlinear Disturbance Observer Based on Genetic Algorithm for Rotary Steering Drilling Stabilized Platform

This study proposed a novel robust sliding mode control strategy for the stabilized platform of rotary steering drilling system. Firstly, a Nonlinear Disturbance Observer (NDO) which can converge exponentially with suitable design parameters is used to observe the uncertain disturbance of stabilized platform under work condition. Subsequently, sliding mode controller is designed to guarantee the robustness of the closed-loop system. The adaptive rate of switching gain is designed and sign function is replaced by bipolar sigmoid function to weaken chattering. Finally, Genetic Algorithm (GA) is applied to search the optimal controller parameters, including switching function coefficient, switching gain adaptive coefficient, sigmoid function coefficient and observer coefficient. Simulation results show that NDO can observe the uncertain disturbance effectively, controller output is decreased and stabilized platform can get optimal control performance and robustness.