TY - GEN
T1 - Path-Tracking Control of the 4WIS4WID Electric Vehicle by Direct Inverse Control using Artificial Neural Network
AU - Kumar, Praveen
AU - Sandhan, Tushar
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Handling the system's nonlinearity is a challenging aspect for the controllers' design. The four-wheel independent steering, four-wheel independent drive (4WIS4WID) electrical vehicle (EV) composes of a pneumatic tire, motors and suspension system, which all are nonlinear. The classical controller is not a suitable choice for a nonlinear system. An autonomous electric vehicle's path-tracking control (PTC) has applications such as autonomous driving, where the vehicle needs to follow a pre-determined trajectory or navigate through a complex environment. The works of literature on path-tracking control schemes are sophisticated to implement on the 4WIS4WID EV. In this paper, the nonlinearity of the plant has been controlled by direct inverse control (DIC) using artificial neural networks (ANN). The use of ANN makes the PTC a simple and effective solution. The simulation results demonstrate the dual enhancement of tracking accuracy and vehicle stability by implementing the proposed controller.
AB - Handling the system's nonlinearity is a challenging aspect for the controllers' design. The four-wheel independent steering, four-wheel independent drive (4WIS4WID) electrical vehicle (EV) composes of a pneumatic tire, motors and suspension system, which all are nonlinear. The classical controller is not a suitable choice for a nonlinear system. An autonomous electric vehicle's path-tracking control (PTC) has applications such as autonomous driving, where the vehicle needs to follow a pre-determined trajectory or navigate through a complex environment. The works of literature on path-tracking control schemes are sophisticated to implement on the 4WIS4WID EV. In this paper, the nonlinearity of the plant has been controlled by direct inverse control (DIC) using artificial neural networks (ANN). The use of ANN makes the PTC a simple and effective solution. The simulation results demonstrate the dual enhancement of tracking accuracy and vehicle stability by implementing the proposed controller.
KW - 4WIS4WID EV
KW - Artificial neural network
KW - Autonomous driving
KW - Direct inverse control
KW - Non-linearity of a system
KW - PTC
UR - http://www.scopus.com/inward/record.url?scp=85179840950&partnerID=8YFLogxK
U2 - 10.1109/ICCCNT56998.2023.10306595
DO - 10.1109/ICCCNT56998.2023.10306595
M3 - Conference contribution
AN - SCOPUS:85179840950
T3 - 2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023
BT - 2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023
Y2 - 6 July 2023 through 8 July 2023
ER -