Path-Tracking Control of the 4WIS4WID Electric Vehicle by Direct Inverse Control using Artificial Neural Network

Praveen Kumar; Tushar Sandhan

doi:10.1109/ICCCNT56998.2023.10306595

Path-Tracking Control of the 4WIS4WID Electric Vehicle by Direct Inverse Control using Artificial Neural Network

Praveen Kumar, Tushar Sandhan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

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.

Original language	English
Title of host publication	2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350335095
DOIs	https://doi.org/10.1109/ICCCNT56998.2023.10306595
State	Published - 2023
Externally published	Yes
Event	14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023 - Delhi, India Duration: Jul 6 2023 → Jul 8 2023

Publication series

Name	2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

Conference

Conference	14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023
Country/Territory	India
City	Delhi
Period	07/6/23 → 07/8/23

Funding

We express our gratitude to the Ministry of Electronics and Information Technology, Government of India (MeitY), for funding this work under the project “Robotics and Automation in Agriculture,” with the reference number 4(16)/2019-ITEA.

Keywords

4WIS4WID EV
Artificial neural network
Autonomous driving
Direct inverse control
Non-linearity of a system
PTC

Access to Document

10.1109/ICCCNT56998.2023.10306595

Cite this

Kumar, P., & Sandhan, T. (2023). Path-Tracking Control of the 4WIS4WID Electric Vehicle by Direct Inverse Control using Artificial Neural Network. In 2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023 (2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCCNT56998.2023.10306595

Kumar, Praveen ; Sandhan, Tushar. / Path-Tracking Control of the 4WIS4WID Electric Vehicle by Direct Inverse Control using Artificial Neural Network. 2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023).

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title = "Path-Tracking Control of the 4WIS4WID Electric Vehicle by Direct Inverse Control using Artificial Neural Network",

abstract = "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.",

keywords = "4WIS4WID EV, Artificial neural network, Autonomous driving, Direct inverse control, Non-linearity of a system, PTC",

author = "Praveen Kumar and Tushar Sandhan",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023 ; Conference date: 06-07-2023 Through 08-07-2023",

year = "2023",

doi = "10.1109/ICCCNT56998.2023.10306595",

language = "English",

series = "2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023",

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Kumar, P & Sandhan, T 2023, Path-Tracking Control of the 4WIS4WID Electric Vehicle by Direct Inverse Control using Artificial Neural Network. in 2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023. 2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023, Institute of Electrical and Electronics Engineers Inc., 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023, Delhi, India, 07/6/23. https://doi.org/10.1109/ICCCNT56998.2023.10306595

Path-Tracking Control of the 4WIS4WID Electric Vehicle by Direct Inverse Control using Artificial Neural Network. / Kumar, Praveen; Sandhan, Tushar.
2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Kumar, Praveen

AU - Sandhan, Tushar

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.

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Kumar P, Sandhan T. Path-Tracking Control of the 4WIS4WID Electric Vehicle by Direct Inverse Control using Artificial Neural Network. In 2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023). doi: 10.1109/ICCCNT56998.2023.10306595

Path-Tracking Control of the 4WIS4WID Electric Vehicle by Direct Inverse Control using Artificial Neural Network

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