Design and Simulation of Anti-interference Control Method for UAVs in Underground Navigation Free Environment

The precise trajectory tracking control of rotary wing unmanned aerial vehicles (UAVs) is crucial for safe navigation in complex interference environments such as coal mine tunnels and fully mechanized working faces. In order to find a control algorithm that is more suitable for the above environment than PID, this paper empirically compares three control frameworks: PID, nonlinear dynamic inversion, and model prediction based on observation compensation by tracking the real-time motion planning trajectory of the designed multi obstacle unmanned aerial vehicle. Build a tunnel environment map in the Gzebo virtual simulation environment, and systematically evaluate and compare the flight performance of unmanned aerial vehicles under several control frameworks in terms of tracking accuracy, robustness, and computational efficiency. The simulation results show that the simulation results of Incremental Nonlinear Dynamic Inversion (INDI) and Disturbance Observer Model Predictive Control (DOMPC) are ideal and can be used as flight control strategies for underground coal mines, but DOMPC is more ideal.