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Automation of front-end loaders: electronic self leveling and payload estimation
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

A growing population is driving automatization in agricultural industry to strive for more productive arable land. Being part of this process, this work is aimed to investigate the possibility to implement sensor-based automation in a particular system called Front End Loader, which is a lifting arms that is commonly mounted on the front of a tractor. Two main tasks are considered here, namely Electronic Self Leveling (ESL) and payload estimation. To propose commercially implementable solutions for these tasks, specific objectives are set, which are: 1) to propose a controller to perform ESL under typical disturbances 2) to propose a methodology for payload estimation considering realistic estimation conditions. Lastly, aligned with these goals, 3) to propose models for the Front End Loader under consideration for derivation of solutions of the specified tasks.

The self-leveling task assists farmers in maintaining the angular position of the mounted implements, e.g. a bale handler or a bucket, with respect to the ground when the loader is manually lifted or lowered. Experimental results show that different controllers are required in lifting and lowering motions to maintain the implement's angular position with a required accuracy due to principle differences in gravity impact. The gravity helps the necessary correction in lifting motion, but works against the correction in lowering motions. This led us to propose a controller with a proportional term, a discontinuous term and an on-line disturbance estimation and compensation as well as the tuning procedure to achieve a 2 degrees tracking error for lowering motions in steady state. The proposed controller shows less sensitive performance to lowering velocity, as the main disturbance, in comparison to a linear controller.

The second task, payload estimation, assists farmers to work within safety range as well as to work with a weight measurement tool. A mechanical model derived based on equations of motion is improved by a pressure based friction to sufficiently accurately represent the motion of the front end loader under consideration. The proposed model satisfies the desired estimation accuracy of 2\% full scale error in a certain estimation condition domain in constant velocity regions, with off-line calibration step and off-line payload estimation step. An on-line version of the estimation based on Recursive Least Squares also fulfills the desired accuracy, while keeping the calibration step off-line.

Place, publisher, year, edition, pages
Umeå: Umeå University , 2017. , 64 p.
Series
Robotics and control lab, ISSN 1654-5419 ; 8
Keyword [en]
Front-End Loaders, Electronic Self Leveling, Modeling, Control, Disturbance estimation, Payload estimation, Equations of motion, Pressure-based friction
National Category
Control Engineering Robotics
Identifiers
URN: urn:nbn:se:umu:diva-134338ISBN: 978-91-7601-709-8 (print)OAI: oai:DiVA.org:umu-134338DiVA: diva2:1092272
Public defence
2017-05-26, N420, Naturvetarhuset, Umeå universitet, Umeå, 13:00 (English)
Opponent
Supervisors
Available from: 2017-05-05 Created: 2017-05-02 Last updated: 2017-05-08Bibliographically approved
List of papers
1. Automation of Front End Loaders: Self Leveling Task
Open this publication in new window or tab >>Automation of Front End Loaders: Self Leveling Task
2015 (English)In: 20th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2015). Luxembourg City, 08 - 11 September 2015, 2015, 1-7 p.Conference paper, Published paper (Refereed)
Abstract [en]

Due to some limitations of mechanical solution for automation of front end loaders, specifically self-leveling task, we investigate here the sensor-based solution. We present a model of ront end loaders and the comparison of different controllers to realize this task. The best performance is observed from the controller comprising linear terms, compensation of input nonlinearity known as dead zone, and compensation of disturbances from its estimation.

National Category
Control Engineering
Research subject
Automatic Control
Identifiers
urn:nbn:se:umu:diva-113696 (URN)10.1109/ETFA.2015.7301451 (DOI)000378564800052 ()9781467379304 (ISBN)
Conference
20th IEEE International Conference on Emerging Technologies and Factory Automation, Luxembourg City, 08 - 11 September 2015
Funder
Swedish Research Council, 2012-4172
Available from: 2015-12-22 Created: 2015-12-22 Last updated: 2017-05-02Bibliographically approved
2. Control and Tuning Procedure of a Cylinder in Mobile Hydraulics
Open this publication in new window or tab >>Control and Tuning Procedure of a Cylinder in Mobile Hydraulics
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Automation of various agricultural tasks, which are routinely executed nowadays by operators of hydraulically actuated tractors equipped with front-end loaders, is an important open problem. The so-called self leveling task is considered here, where the lifting and lowering motions of the loader are performed manually while the orientation of the implement must be adjusted automatically. The proposed controller is constituted by a proportional feedback, a compensator based on a disturbance observer and a relay controller. A tuning procedure for parameters is discussed and an implementation is validated experimentally on an industry-standard commercial set-up.

National Category
Control Engineering
Identifiers
urn:nbn:se:umu:diva-134340 (URN)
Note

Submitted

Available from: 2017-05-02 Created: 2017-05-02 Last updated: 2017-05-04
3. Payload Estimation in Front-End Loaders
Open this publication in new window or tab >>Payload Estimation in Front-End Loaders
2016 (English)Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
IEEE, 2016
National Category
Robotics
Identifiers
urn:nbn:se:umu:diva-130587 (URN)
Conference
MCG 2016 – 5th International Conference on Machine Control & Guidance
Available from: 2017-01-24 Created: 2017-01-24 Last updated: 2017-05-04
4. Improvement of Model-Based Payload Estimation for Agricutural Front-End Loaders
Open this publication in new window or tab >>Improvement of Model-Based Payload Estimation for Agricutural Front-End Loaders
(English)Manuscript (preprint) (Other academic)
Abstract [en]

We consider here the development of a better payload estimation system for an agricultural Front-End Loader, equipped with position and pressure sensors, that enable monitoring of various routine operations. We show that an additional pressure-based friction model improves the achievable accuracy of the estimation procedure for payload estimation based on equations of motion. Preceded by estimating the friction parameters in the calibration step, the improvement is verified by employing the updated model in off-line payload estimations for an industry standard Front-End Loader with different estimation conditions under consideration. The overall estimation accuracy is below 2% full scale error. This performance is also maintained in the online implementation of the second step.

National Category
Robotics
Identifiers
urn:nbn:se:umu:diva-134341 (URN)
Available from: 2017-05-02 Created: 2017-05-02 Last updated: 2017-05-04

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