Development of an RLS based all-wheel steering algorithm for path tracking of mobility in smart farm with gain self-tuning

Jinseok Kang; Eungyu Lee; Donghee Ko; Wonyeop Park; Kwangseok Oh

doi:10.22765/pastj.20250019

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2025 Vol.7, Issue 3 Preview Page Next Page

Research Article

Development of an RLS based all-wheel steering algorithm for path tracking of mobility in smart farm with gain self-tuning

30 September 2025. pp. 264-273

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Abstract

For improving the efficiency of crop production in smart farm, periodical monitoring of crop ripeness level and harvesting at the proper time are essential. For periodical monitoring of crops, this study proposes path generation and all-wheel steering control algorithms of path tracking of mobility in smart farm. Error dynamics with coefficients that represents dynamic characteristics of mobility has been designed for determination of front and rear wheel angles. The coefficients in error dynamics have been estimated based on recursive least squares with multiple forgetting factors. The estimated coefficients have been used to compute the steering control inputs in real-time based on Lyapunov direct method. To adjust the level of engagement of the rear wheel control input, parameter of reduction gain for rear wheel control input has been self-tuned using yaw angle error. The path generation algorithm for smart farm has been designed based on waypoint and it has been used for performance evaluation. The performance evaluation was conducted with the co-simulation of Matlab/Simulink and CarMaker. The results showed that the mobility can track the generated path reasonably with various evaluation cases. It was confirmed that the proposed steering control algorithm can reduce the yaw angle error with rear wheel steering. The proposed algorithm can facilitate path generation and steering control for smart farm mobility. This is expected to lead to periodic crop monitoring within smart farm facilities, automation of various tasks within smart farms, and utilization of monitoring data to control various facilities and environments, resulting in increased productivity and reduced labor costs.

Keywords

Gain self-tuning

Path tracking

Recursive least squares

Smart farm

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Information

Publisher :Korean Society of Precision Agriculture
Publisher(Ko) :한국정밀농업학회
Journal Title :Precision Agriculture Science and Technology
Journal Title(Ko) :정밀농업과학기술
Volume : 7
No :3
Pages :264-273
Received Date : 2025-09-05
Revised Date : 2025-09-26
Accepted Date : 2025-09-27
DOI :https://doi.org/10.22765/pastj.20250019

Precision Agriculture Science and Technology ISSN:2672-0086(Print) 2713-5632(Online) 정밀농업과학기술

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