A feed-forward control method for unmanned vehicle path tracking
A technology of path tracking and feedforward control, applied in adaptive control, general control system, control/regulation system, etc., can solve problems such as high algorithm complexity, prediction error, and inability to predict the curvature of the road ahead, and achieve application prospects Good, simple algorithm effect
Active Publication Date: 2021-03-05
四川智动木牛智能科技有限公司
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However, this method only compensates for changes in road curvature by previewing a single far point. The reference path information is insufficient to accurately predict the curvature of the road ahead, and it does not consider neural response delays and human action mechanisms, resulting in certain prediction errors.
The improved model predictive control (MPC) based on online learning of Gaussian sparse process proposed by Taewan Kim is a special optimal control method with good control effect, but due to the high complexity of its algorithm, this method can only be applied to In the field of simulation technology, it is difficult to implement on the real vehicle embedded controller
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[0044] The overall design idea of the present invention is: add the road curvature as the disturbance input item in the traditional vehicle path tracking system model, give the system model state space expression after adding the curvature disturbance, and aim at the lateral position deviation of zero for the new model Function design feed-forward control method. In the actual vehicle test, according to the road curvature prediction method based on least squares fitting, combined with the feedforward control method, the expected front wheel angle of the unmanned vehicle is obtained in real time.
[0045] Before introducing the implementation steps of the present invention, first introduce the technical principle of the present invention. The technical principle includes the following steps:
[0046] Step 1: Based on the two-degree-of-freedom dynamics model of the vehicle, combined with the traditional unmanned vehicle path tracking system model, the road curvature is added ...
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The invention provides a driverless car path tracking feedforward control method. The method includes the following steps: road curvature is added to a traditional vehicle path tracking system model as an interference input item, and a system model state space expression after adding the curvature interference is given. Aiming at the model, the feedforward control method is designed with the transverse position deviation tending to zero as a target function. The method is simple in algorithm, is suitable for the simulation technical field, can be realized on a real vehicle embedded controller,and has good application prospect.
Description
technical field [0001] The invention relates to the field of automatic control of unmanned vehicles, in particular to a path tracking feedforward control method for unmanned vehicles. Background technique [0002] Unmanned vehicle path tracking control refers to the lateral control of unmanned vehicles, that is, through automatic steering control, the vehicle can always drive along the desired path autonomously, while ensuring the driving safety and riding comfort of the vehicle. Precise control for path tracking is a prerequisite for autonomous and stable autonomous vehicle operation. Feedforward control means that by predicting the disturbance that will be generated in the future, control measures are taken in advance according to the magnitude of the disturbance to compensate for the influence of the disturbance on the controlled variable, so that the controlled variable will not be deviated due to the disturbance. [0003] At present, many researchers at home and abroad...
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IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 蒋涛刘奕杰
Owner 四川智动木牛智能科技有限公司