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 -