NMPC-Based Anti-Disturbance Control of UAM

This paper addresses the challenge of stabilizing an unmanned aerial vehicle with an arm (UAM) on a pipeline with disturbance, where the disturbance factors include white noise, mass uncertainty, and wind disturbance. An anti-disturbance control method is proposed utilizing nonlinear model predictive control (NMPC). Initially, the natural wind field model is developed. Considering wind disturbance, the UAM dynamics are analyzed utilizing Newton–Euler theory. Subsequently, the no-slip constraints and the terminal constraints are defined to prevent UAM from destabilizing and falling. The NMPC-based algorithm is developed to ensure the stable control of UAM, transforming the optimization problem into a nonlinear programming problem. The terminal cost function and the inequality constraints for establishing the state variables using linear quadratic regulator (LQR) are meticulously studied. Finally, numerical simulations are carried out to further verify the proposed method, considering internal disturbance about physical parameters and external disturbance about wind. Simulation results show that the disturbance is well compensated, and the UAM tilt angle is less than 0.3 deg. Therefore, the proposed control method can comprehensively consider the input energy consumption and the realization of stability, and has a certain degree of anti-interference.