Linear model predictive control of automatic parking path tracking with soft constraints

This study examines how to improve the accuracy of auto parking path tracking control; therefore, a linear model predictive control with softening constraints path tracking control strategy is proposed. Firstly, a linear time-varying predictive model of vehicle is established, and the future state o...

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Bibliographic Details
Published in:International journal of advanced robotic systems 2019-05, Vol.16 (3)
Main Authors: Ye, Hao, Jiang, Haobin, Ma, Shidian, Tang, Bin, Wahab, Lukuman
Format: Article
Language:English
Subjects:
Algorithms
Automatic control
Computer simulation
Constraint modelling
Control algorithms
Control theory
Differentiation
Mathematical analysis
Optimization
Parking
Path tracking
Predictive control
Quadratic programming
Tracking control
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Summary:This study examines how to improve the accuracy of auto parking path tracking control; therefore, a linear model predictive control with softening constraints path tracking control strategy is proposed. Firstly, a linear time-varying predictive model of vehicle is established, and the future state of the vehicle can be predicted. The designed objective function fully considers the deviation between the predictor variable and the reference variable. Also, the relaxation factors are added to the optimization process, and the control increment of each cycle is calculated by the quadratic programming. Through rolling optimization and feedback correction, all kinds of deviations in the control process can be corrected in time. Then, the Simulink/CarSim simulation is carried out jointly. Furthermore, the path tracking simulation based on proportion–integration–differentiation control and no control is also carried out to compare with the model predictive control. Finally, a real vehicle test is carried out for model predictive control algorithm, and a comparative experiment based on proportion–integration–differentiation control and no control is carried out.
ISSN:1729-8806
1729-8814
DOI:10.1177/1729881419852201