Vehicle transverse and longitudinal coupling nonlinear model prediction controller based on parallel Newton solution

Abstract

The invention discloses a vehicle transverse and longitudinal coupling nonlinear model prediction controller based on parallel Newton solution, which obtains a transverse and longitudinal coupling nonlinear control model through a vehicle three-degree-of-freedom kinetic model, and by adopting a front wheel steering angle and front and rear wheel driving force as control variables, according to a model prediction control algorithm, vehicle physical constraints are considered and a cost function is constructed. Aiming at the vehicle path tracking control problem, a transverse and longitudinal coupling control model is obtained by using vehicle dynamics, a nonlinear model prediction controller is designed by using the model, and rapid solution of the nonlinear controller is realized by usinga parallel Newton method. The vehicle transverse and longitudinal coupling path tracking nonlinear model prediction controller is derived through a vehicle three-degree-of-freedom kinetic model, the mutual influence between the transverse direction and the longitudinal direction is considered, the nonlinear prediction controller is designed according to the model, the nonlinearity of a vehicle system is reserved, and the model precision is ensured.

Description

technical field [0001] The invention relates to a horizontal and vertical coupling control system in the field of intelligent vehicle automatic driving and a fast calculation method thereof, in particular to a vehicle horizontal and vertical coupling nonlinear model predictive controller based on parallel Newton solution. Background technique [0002] The automatic driving system mainly includes three parts: perception, planning and control. Among them, the vehicle path tracking control system is one of the core links, which has strong research significance and application value. Path tracking control achieves precise tracking of the desired path by controlling the corresponding chassis actuators according to the desired driving path given by the planning system and the state information fed back by the vehicle in real time. Therefore, how to design the controller so that the vehicle can quickly realize the tracking of the desired path, while ensuring real-time performance, ...

AI Technical Summary

Problems solved by technology

[0003] 1. The structure of the vehicle system is complex, especially under complex extreme working conditions, it shows strong nonlinearity, multi-dimensional motion and high coupling, etc. The controller established based on the vehicle linear model ignores many dynamic characteristics, and it is difficult to meet the control requirements of the system. Accuracy requirements

[0004] 2. Although the model predictive controller designed based on the nonlinear model of the vehicle retains the nonlinear and dynamic characteristics of the vehicle, it causes a large computational burden

In the traditional solution method, due to the coupling relationship between the state quantities, the solution in the prediction time domain cannot be independent, and the overall calculation is required. With the increase of the prediction time domain, the solution time is difficult to meet the real-time requirements of the system

Images