Research on the motion control of an unmanned ammunition supply vehicle based on model predictive control
In response to the problem of low tracking precision and poor stability caused by the larger size and weight of unmanned ammunition supply vehicles and the greater centrifugal force experienced in wild conditions with large curves,we established a dynamic model of the unmanned ammunition supply vehicle.Based on the traditional model predictive control algorithm,we incorporated dynamic constraints of center of gravity lateral deviation angle,vehicle adhesion coefficient,and tire lateral deviation angle.Suitable input,output,and state variables were selected to build a prediction control model and complete algorithm design.The improved model predictive control algorithm was verified through joint simulations and real vehicle tests.The results analysis revealed that compared to the traditional control algorithm,the proposed control algorithm demonstrated higher stability and tracking precision for unmanned ammunition supply vehicles in wild conditions with large curves,meeting the performance requirements for lateral control of unmanned ammunition supply vehicles.
unmanned vehiclemodel predictive controlpath trackingdynamic model
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