2021/12/03 by Damla Leblebicioğlu, Leblebicioglu, Damla, Özgür Atesoglu +3
Engineering · #Advanced Control and Stabilization in Aerospace Systems #FOS: Electrical engineering #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2112.02130
openalex publication_date 2021/12/03 · openalex created_date 2021/12/31 · openalex updated_date 2026/07/28
The increasing demand for target tracking, environmental surveys, surveillance and mapping requires multi-axis gimbal systems with high tracking and stabilization performance. In this paper, first, computed torque model is generated to estimate the complex disturbances acting on the system. Then, two different control strategies based on active disturbance rejection control (ADRC) and computed torque model are implemented on a two-axis gimbal system. The purpose is to improve the robustness, environmental adaptability and tracking accuracy of the system and reduce the tuning effort of ADRC by integrating a neural network (NN) based disturbance compensator (NN assisted ADRC). In the second control strategy, NN is replaced with a computed torque model (CTM assisted ADRC), whose inputs come from plant outputs. The simulation results show that, NN and CTM assisted ADRC structures can decrease mean tracking errors up to 85.4% and 40.8%, respectively.