TY - JOUR
T1 - Fast warm-start of F-MPC strategy for automotive cruise control with mode switching
AU - Liu, Jiaqi
AU - Dong, Shiying
AU - Liu, Qifang
AU - Gao, Bingzhao
AU - Kawabe, Taketoshi
AU - Chen, Hong
N1 - Funding Information:
This document is funded by 1. Shanghai Municipal Science and Technology Major Project, China (2021SHZDZX0100) 2. China Automobile Industry Innovation and Development Joint Fund (U1864206) 3. International Technology Cooperation Program of Science and Technology Commission of Shanghai Municipality (21160710600) 4. Jilin Provincial Science & Technology Department (20200301011RQ).
Funding Information:
This document is funded by 1. Shanghai Municipal Science and Technology Major Project, China ( 2021SHZDZX0100 ) 2. China Automobile Industry Innovation and Development Joint Fund ( U1864206 ) 3. International Technology Cooperation Program of Science and Technology Commission of Shanghai Municipality ( 21160710600 ) 4. Jilin Provincial Science & Technology Department ( 20200301011RQ ).
Publisher Copyright:
© 2022
PY - 2022/11
Y1 - 2022/11
N2 - A fast iterative algorithm of nonlinear model predictive control is proposed to solve the warm-start problem of the fast model predictive control (F-MPC) method for real-time application with mode switching. Because an incorrect initial guess of F-MPC creates problems such as excessive iterations or even solution failures, the proposed iterative algorithm aims to provide the initial value of F-MPC quickly and efficiently. The idea is to decompose the original nonlinear system into a main linear part and a nonlinear part, which is regarded as measurable disturbance. Then the explicit optimal solution of the “disturbed” system is derived, the obtained series of control inputs are applied to the system, the system state and consequently the “disturbance” are updated, and finally the process is repeated until convergence. The calculated iterative result can be used as the initial solution for F-MPC especially for maneuver mode switching. Automotive cruise control is used as an example for validation, and it is shown that the control strategy has superior adaptability for mode switching, guaranteeing the given safety constraints as well as significantly reducing the computational load.
AB - A fast iterative algorithm of nonlinear model predictive control is proposed to solve the warm-start problem of the fast model predictive control (F-MPC) method for real-time application with mode switching. Because an incorrect initial guess of F-MPC creates problems such as excessive iterations or even solution failures, the proposed iterative algorithm aims to provide the initial value of F-MPC quickly and efficiently. The idea is to decompose the original nonlinear system into a main linear part and a nonlinear part, which is regarded as measurable disturbance. Then the explicit optimal solution of the “disturbed” system is derived, the obtained series of control inputs are applied to the system, the system state and consequently the “disturbance” are updated, and finally the process is repeated until convergence. The calculated iterative result can be used as the initial solution for F-MPC especially for maneuver mode switching. Automotive cruise control is used as an example for validation, and it is shown that the control strategy has superior adaptability for mode switching, guaranteeing the given safety constraints as well as significantly reducing the computational load.
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U2 - 10.1016/j.conengprac.2022.105344
DO - 10.1016/j.conengprac.2022.105344
M3 - Article
AN - SCOPUS:85138017487
SN - 0967-0661
VL - 128
JO - Control Engineering Practice
JF - Control Engineering Practice
M1 - 105344
ER -