TY - GEN
T1 - Adaptive Cruise Control by Considering Control Decision as Multistage MPC Constraints
AU - Miftakhudin, Muhamad Ilfani
AU - Subiantoro, Aries
AU - Yusivar, Feri
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - In designing of original adaptive cruise control (ACC) systems the outer loop is commonly used to control the safe distance between host and lead vehicles, and the inner loop maintains the speed of host vehicle. The aim of this paper is to propose different approach, in which only a single loop is introduced as controller. A decision algorithm for determining a driving mode is designed as part of multistage model predictive control constraints. The nonlinear behavior of vehicle dynamic is represented by a multistage local linear model, which will be identified by using least squares method. The objective of multistage predictive control is to minimized the square of errors between the predicted values of vehicle speed and the safety distance, and their references. The proposed controller demonstrates to more efficient in terms of power computing, it is because the method can keep the optimization control problem as a quadratic programming problem. Some ACC simulation results are given, demonstrating a better performance in terms of distance and speed responses compared to the original ACC system.
AB - In designing of original adaptive cruise control (ACC) systems the outer loop is commonly used to control the safe distance between host and lead vehicles, and the inner loop maintains the speed of host vehicle. The aim of this paper is to propose different approach, in which only a single loop is introduced as controller. A decision algorithm for determining a driving mode is designed as part of multistage model predictive control constraints. The nonlinear behavior of vehicle dynamic is represented by a multistage local linear model, which will be identified by using least squares method. The objective of multistage predictive control is to minimized the square of errors between the predicted values of vehicle speed and the safety distance, and their references. The proposed controller demonstrates to more efficient in terms of power computing, it is because the method can keep the optimization control problem as a quadratic programming problem. Some ACC simulation results are given, demonstrating a better performance in terms of distance and speed responses compared to the original ACC system.
KW - adaptive cruise control
KW - model predictive control
KW - multistage identification
KW - vehicle modeling
UR - http://www.scopus.com/inward/record.url?scp=85084417977&partnerID=8YFLogxK
U2 - 10.1109/CENCON47160.2019.8974766
DO - 10.1109/CENCON47160.2019.8974766
M3 - Conference contribution
AN - SCOPUS:85084417977
T3 - CENCON 2019 - 2019 IEEE Conference on Energy Conversion
SP - 171
EP - 176
BT - CENCON 2019 - 2019 IEEE Conference on Energy Conversion
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE Conference on Energy Conversion, CENCON 2019
Y2 - 16 October 2019 through 17 October 2019
ER -