Heading control of variable configuration unmanned ground vehicle using PID-type sliding mode control and steering control based on particle swarm optimization

When performing tasks in the field, the unmanned ground vehicle (UGV) usually requires the ability of quickly adjusting the driving direction, and realizing the flexible motion control to deal with emergencies. In order to achieve the rapid adjustment of driving direction of the six-wheel independent drive and four independent steering unmanned ground vehicle with variable configuration, an adaptive counter-rotation hierarchical control strategy is proposed in this paper. Based on the expected yaw angle, the upper controller estimates the required yaw moment using PID-type sliding mode control, and constructs the function of structural and unstructured parameters as lumped uncertainty. Then, the sideslip angle of each tire is optimized by using PSO algorithm with the adaptive weight, and the influence of structural uncertainty is eliminated by the adaptive control of independent steering. In the lower controller, the desired yaw moment is distributed to six electric motors according to the vertical load. Finally, co-simulation under different operation conditions is carried out to verify the feasibility and effectiveness of the proposed strategy. The simulation results show that the presented strategy enables the variable configuration UGV quickly adjust the driving direction, and has relatively good adaptability to the changes of the wheelbase and the track width.

Automated summary

An adaptive counter-rotation hierarchical control strategy is proposed in this paper to achieve the rapid adjustment of driving direction for a six-wheel independent drive and four independent steering unmanned ground vehicle with variable configuration. The strategy is validated through co-simulation under different operation conditions.