Trajectory tracking for aircraft tug based on MPC

To meet the short and high frequency demands of quick aircraft towing at logistics airports, a rapid towing method based on unmanned driving technology is proposed. Using the technical route and method of “theoretical modeling-algorithm design-case test and simulation optimization-prototype experiment”, a kinematic model of the towing vehicle is constructed for a 10-ton aircraft towing vehicle, the vehicle’s constraint conditions and control quantities are determined, and the A^* algorithm is improved by adding collision avoidance processing, minimum turning radius, and path smoothing to generate the motion trajectory of the towing vehicle. A trajectory tracking controller based on model predictive control (MPC) is designed, and a joint simulation model of MATLAB/Simulink and ADAMS is constructed. The control parameters of MPC are optimized through trajectory tracking simulation experiments, and trajectory tracking experiments are carried out on the modified electric aircraft towing vehicle prototype. The results show that the improved A^* algorithm meets the requirements of aircraft towing vehicle work path planning and minimum turning radius, the joint simulation method optimizes the MPC controller, achieves good tracking accuracy on the prototype, with standard deviation of tracking errors for curve paths and straight paths being 0.362 m and 0.128 m respectively, realizes the unmanned driving function of the aircraft towing vehicle, and lays the technical foundation for unmanned aircraft towing at smart logistics airports.