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On-line Access: 2020-10-14

Received: 2019-10-30

Revision Accepted: 2020-02-21

Crosschecked: 2020-08-28

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Citations:  Bibtex RefMan EndNote GB/T7714


Xiao-lan Yao


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Frontiers of Information Technology & Electronic Engineering  2020 Vol.21 No.10 P.1521-1534


Trajectory optimization with constraints for alpine skiers based on multi-phase nonlinear optimal control

Author(s):  Cong-ying Cai, Xiao-lan Yao

Affiliation(s):  School of Automation, Beijing Institute of Technology, Beijing 100081, China

Corresponding email(s):   yaoxiaolan@bit.edu.cn

Key Words:  Trajectory optimization, Optimal control, Pseudospectral method, Optimal trajectory, Numerical solution

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Cong-ying Cai, Xiao-lan Yao. Trajectory optimization with constraints for alpine skiers based on multi-phase nonlinear optimal control[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(10): 1521-1534.

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%DOI 10.1631/FITEE.1900586

T1 - Trajectory optimization with constraints for alpine skiers based on multi-phase nonlinear optimal control
A1 - Cong-ying Cai
A1 - Xiao-lan Yao
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 21
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.1900586

The super giant slalom (Super-G) is a speed event in alpine skiing, in which the skier trajectory has a significant influence on the athletes’ performances. It is a challenging task to determine an optimal trajectory for the skiers along the entire course because of the complexity and difficulty in the convergence of the optimization model. In this study, a trajectory optimization model for alpine skiers competing in the Super-G is established based on the optimal control theory, in which the objective is to minimize the runtime between the starting point and the finish line. The original trajectory optimization problem is converted into a multi-phase nonlinear optimal control problem solved with a pseudospectral method, and the trajectory parameters are optimized to discover the time-optimal trajectory. Using numerical solution carried out by the MATLAB optimization toolbox, the optimal trajectory is obtained under several equality and inequality constraints. Simulation results reveal the effectiveness and rationality of the trajectory optimization model. A test is carried out to show that our code works properly. In addition, several practical proposals are provided to help alpine skiers improve their training and skiing performance.





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