Dynamic model-based unmanned car model prediction controller design method

A technology of unmanned vehicles and dynamic models, applied in non-electric variable control, two-dimensional position/course control, vehicle position/route/height control, etc., can solve problems such as model state errors and achieve good control effects Effect

Inactive Publication Date: 2019-04-09
TIANJIN UNIV
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Problems solved by technology

The error between the characteristics of the vehicle model and the actual characteristics of the vehi

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  • Dynamic model-based unmanned car model prediction controller design method
  • Dynamic model-based unmanned car model prediction controller design method
  • Dynamic model-based unmanned car model prediction controller design method

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[0052] In order to make the purpose of the present invention, technical solutions and advantages clearer, the establishment of the new vehicle dynamics model, the design principle and solution method of the model predictive controller will be further explained below, and the following specific design methods are used to explain the present invention. invention, but not limited to the present invention.

[0053] The unmanned vehicle model predictive controller design method based on dynamics model of the present invention comprises the following steps:

[0054] Step 1: Establish a new vehicle dynamics model

[0055] Apart from gravity and air resistance, nearly all of the significant forces on a car act directly on the tires. Because of the complexity and nonlinearity of tire forces, choosing an appropriate tire model is crucial for establishing an accurate vehicle dynamics model. The present invention uses the tire lateral force and traction model proposed by Pacejka. The m...

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Abstract

The invention discloses a dynamic model-based unmanned car model prediction controller design method. According to the method, a novel vehicle dynamic model is established; an unmanned car model prediction controller on the basis of the novel vehicle dynamic model; (1) the novel vehicle dynamic model obtained through linearization at the current working point is utilized to predict an output stateof a system in a prediction time domain; (2) the obtained predicted output of the system and given reference output are utilized to construct an optimization problem; and (3) the optimization problemis solved, and a first component of U (k) is taken as an optimal control quantity of the current moment to act on the system. According to the method, vehicle speed is added to serve as the control quantity, and error compensation is introduced to make up accumulative errors caused by model precision, linearization and discretization in the prediction process, so that unmanned cars can have a better trajectory tracing effect.

Description

technical field [0001] The invention belongs to the field of driverless car controller design, and more specifically relates to a dynamic model-based model predictive controller design method for driverless cars. Background technique [0002] In the past few years, as the most important part of artificial intelligence, while benefiting from the development of global positioning system (GPS), radar system and machine vision, unmanned driving has gained wide attention from all walks of life. Unmanned driving can be divided into figure 1 Four parts are shown: global path planning, environment perception, local path planning, and trajectory tracking. Trajectory tracking controller composed of lateral controller and longitudinal controller is an important part of unmanned driving. [0003] At first, scholars used proportional-integral-derivative (PID) controllers to complete the trajectory tracking task. However, because the car is a multiple-input and multiple-output system, ...

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Application Information

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IPC IPC(8): G05B13/04G05D1/02
CPCG05B13/042G05D1/0223
Inventor 左志强杨孟佳王一晶
Owner TIANJIN UNIV
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