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Unmanned vehicle tracking control method and device

An unmanned vehicle, tracking control technology, applied in vehicle position/route/altitude control, control/regulation system, non-electric variable control and other directions, can solve problems such as the inability to meet the real-time tracking control needs of unmanned systems

Pending Publication Date: 2022-05-06
ZHENGZHOU YUTONG BUS CO LTD
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AI Technical Summary

Problems solved by technology

[0004] The present invention provides an unmanned vehicle tracking control method and device, which are used to solve the problem that the control method in the prior art cannot meet the real-time tracking control needs of the unmanned driving system

Method used

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  • Unmanned vehicle tracking control method and device
  • Unmanned vehicle tracking control method and device

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Embodiment Construction

[0048]The invention adopts the explicit model predictive control to control the self-driving vehicle, and its main idea is to use the multi-parameter quadratic programming theory to solve the optimization control problem of the linear time-invariant constraint system. In this method, the state quantity of the system is taken as a parameter, the state area is divided convexly, and the optimal state feedback control rate and state control explicit relational expression of each state partition is calculated off-line. At each sampling moment, according to the state partition where the current system state quantity is located, the corresponding control explicit relational expression is obtained by looking up the table, and the current optimal front wheel angle control quantity is obtained. The explicit model predictive control method does not need repeated online optimization, which can improve the online calculation speed. A tracking control method for an unmanned vehicle and a tr...

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Abstract

The invention belongs to the technical field of unmanned driving, and particularly relates to an unmanned vehicle tracking control method and device. The method comprises the steps that firstly, the current system state quantity of a vehicle is obtained, and a control explicit relational expression corresponding to a system state partition is determined according to the state partition where the current system state quantity is located; the system state quantity comprises a first-order derivative of longitudinal displacement under a vehicle body coordinate system, a first-order derivative of transverse displacement under the vehicle body coordinate system, a yaw angle, a first-order derivative of the yaw angle, longitudinal displacement under an inertial coordinate system and transverse displacement under the inertial coordinate system, and then substituting the current system state quantity into the control explicit relational expression, obtaining a current optimal front wheel steering angle control quantity corresponding to the current system state quantity; and finally, controlling the operation of the vehicle by referring to the current optimal front wheel steering angle control quantity. According to the method, repeated online calculation is simplified into simple table look-up work, so that the online calculation time is greatly shortened, the real-time performance of system control is improved, and the tracking precision is ensured.

Description

technical field [0001] The invention belongs to the technical field of unmanned driving, and in particular relates to an unmanned vehicle tracking control method and device. Background technique [0002] Tracking control technology, as one of the key technologies of the unmanned driving system, enables the vehicle to reach a given or planned trajectory point at a specified time by controlling the vehicle's steering system and braking / driving system, thereby realizing the unmanned driving system of the vehicle. human driving operation. [0003] At present, the mainstream unmanned driving system tracking control technology in the industry includes PID control algorithm, preview control algorithm, feed-forward control algorithm, and traditional model prediction algorithm. The PID control algorithm requires a lot of manual calibration, and the control accuracy cannot be guaranteed in real time. At the same time, when the vehicle state changes, the control accuracy will be great...

Claims

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Application Information

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IPC IPC(8): G05D1/02
CPCG05D1/0212
Inventor 黄琨苏常军陈慧勇
Owner ZHENGZHOU YUTONG BUS CO LTD
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