Lateral Controller Design For Unmanned Ground Vehicles With Model Predictive Control

Over the past few years,unmanned driving has attracted a lot of attention due to its great significance for auto industry,transportation,military,environment and other aspects.A precise tracking effect can not only enhance the safety and reliability of unmanned ground vehicles,but also enable the motion and trajectory planning layer to generate more sophisticated strategies.This thesis focuses on the lateral control of unmanned ground vehicles,which mainly includes the following contents:First,a novel dynamic model-based predictive controller is presented.We propose a novel dynamical model for unmanned vehicles,and then design a linear model predic-tive controller by linearizing and discretizing the model on the current operating point thus realize the lateral control of unmanned ground vehicles.Besides,an error com-pensation,where the error is caused by linearization and discretization of the nonlinear model,is added to improve the control precision.Second,a lateral control strategy combining model predictive control and active disturbance rejection control for unmanned ground vehicles is proposed.A kinetic state error model-based predictive controller is presented for the lateral control of unmanned ground vehicles.We also suggest a fast prediction technique.Based on it,the active dis-turbance rejection control is involved to the lateral controller to eliminate the influence of disturbances caused by model uncertainties,actuator error,and other factors.Finally,the influence of slip angle of tire on lateral control is discussed and a slip angle compensation-based lateral controller for unmanned ground vehicles is designed.To overcome the larger slip angle of tire caused by bad weather or high speed,we propose a model predictive control with slip angle compensation,thereby optimize the control effect of kinematic model-based predictive controller on the premise of rapidity.