The Impact of Control Structure on the Path-Following Control of Unmanned Compaction Rollers

Quanzhi, Xu; Xie, Hui; Song, Kyung‐Sik

doi:10.4271/2020-01-5030

Cited by 5 publications

(7 citation statements)

References 11 publications

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“…In previous work, the DRC was proven to be superior to a well-tuned PID controller in accuracy and robustness. 32 Figure 7 depicts the experimental result, which is the average lateral error comparison between DRC and PID with different GPS installation errors.…”

Section: Controller Assessmentmentioning

confidence: 99%

“…Based on previous research, 32 in this section, the performance of CDRC was verified by comparison with DRC in the step response test and disturbance rejection test. The design of the experiments is illustrated below.…”

Section: Controller Assessmentmentioning

confidence: 99%

“…In previous work, the DRC was proven to be superior to a well-tuned PID controller in accuracy and robustness. 32 (3) The third test was a comprehensive test, where a complete rockfill zone was compacted using CDRC.…”

Section: Controller Assessmentmentioning

confidence: 99%

“…To achieve this, active disturbance rejection control (ADRC), as an emerging control technology, has drawn great attention over the past years, and a cascaded ADRC (abbreviated as DRC to distinguish) was proposed in authors’ previous work. 32 However, the DRC showed that it cannot guarantee satisfactory control performance when the roller operates in vibration mode or when the road condition is poor, although the DRC is superior to a model-based PID in accuracy and robustness.…”

Section: Introductionmentioning

confidence: 99%

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Layered disturbance rejection path-following control with geometry-based feedforward for unmanned rollers

Xie

Quanzhi

Song

2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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As a widely used engineering vehicle, drum rollers have a higher degree of freedom in motion than conventional passenger vehicles. The uncertainties, caused by road and vehicle condition variations, introduce severe disturbances in the path-following control of unmanned rollers. In this work, a single-drum roller is considered, for which a composite disturbance rejection controller (CDRC) is proposed for path following. The CDRC comprises a disturbance rejection controller (DRC) and a modified pure pursuit controller (MPPC). The DRC lumps all the discrepancies of the models from the roller as total disturbance, which is estimated by the extended state observer (ESO) and rejected in the feedback control loop. For enhanced performance, MPPC is added as a feedforward controller, which calculates the target articulation angle based on the roller geometry model. Compared with the DRC, the settling time of the CDRC is reduced by 12.3%, and the lateral errors are reduced by 43.1% and 39.9% in the presence of uncertainties in the positioning system and steering motor, respectively, while it still maintains a low computational cost. The proposed controller have been used in 15 unmanned rollers for 2 years, using which over 5 million square meters area has been compacted.

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Section: Controller Assessmentmentioning

confidence: 99%

Section: Controller Assessmentmentioning

confidence: 99%

Section: Controller Assessmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Layered disturbance rejection path-following control with geometry-based feedforward for unmanned rollers

Xie

Quanzhi

Song

2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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“…Yao et al [24] discussed the steering kinematics of a road roller, and proposed a trajectory tracking method with disturbance-resistant and heading estimation. The impact of attitude feedback and control structure on the path following control of unmanned road rollers have been analyzed in [25] and [26] respectively. Chen et al [27] proposed an active disturbance rejection control, featured with estimating and cancelling "total disturbance".…”

Section: Introductionmentioning

confidence: 99%

Path Tracking Control of an Articulated Road Roller With Sideslip Compensation

et al. 2020

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He has presided over the National High Technology Research and Development Program, the National Natural Science Foundation and more than twenty research projects of provincial and ministerial level. He has authored more than fifty academic articles. His research interests include intelligent construction robot and emergency rescue equipment. HAO ZHANG received the M.S. degree in automatic control from Xi'

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Parameter self‐learning feedforward compensation‐based active disturbance rejection for path‐following control of self‐driving forklift trucks

Xie

Song

et al. 2023

Asian Journal of Control

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In this paper, for self‐driving forklift, a path‐following framework based on composite disturbance rejection that combines a cascaded active disturbance rejection controller and an online estimator of model parameters is proposed on the basis of a geometry feedforward controller. The model‐based cascaded active disturbance rejection control (ADRC), in particular, is composed of an outer‐loop controller and an inner‐loop controller, with the outer‐loop controller reducing lateral error by manipulating the desired heading direction and the inner‐loop controller achieving heading control by adjusting the steering angle. The unmodeled dynamics of the actual forklift motion are denoted as total disturbances, which can be timely estimated by the extended state observer (ESO). Moreover, to increase the transient response, a parameter self‐learning based geometry feedforward controller is designed in conjunction with the forklift characteristics. The stability analysis is presented and the effectiveness of the composite algorithm is quantitatively evaluated in experiments, demonstrating the superiority over the conventional pure pursuit algorithm and the only use of ADRC.

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The Impact of Control Structure on the Path-Following Control of Unmanned Compaction Rollers

Cited by 5 publications

References 11 publications

Layered disturbance rejection path-following control with geometry-based feedforward for unmanned rollers

Layered disturbance rejection path-following control with geometry-based feedforward for unmanned rollers

Path Tracking Control of an Articulated Road Roller With Sideslip Compensation

Parameter self‐learning feedforward compensation‐based active disturbance rejection for path‐following control of self‐driving forklift trucks

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