An Optimal Controller for Trajectory Tracking of Automated Guided Vehicle
A trajectory tracking strategy for an Automated Guided Vehicle (AGV) is presented in this paper, containing a hybrid algorithm of a preview feedforward control and a feedback control via linear quadratic regulator (LQR). The purpose of trajectory tracking is to decrease the position and orientation errors between the trajectory and AGV. The vehicle - road dynamics model applied to establish the relationship between vehicle and trajectory and accurately describes plant motion. The preview feedforward control is adopted to solve time delay of steering mechanism in trajectory tracking. The feedback control via LQR is applied to decrease the errors caused by environmental disturbances. For real-time embedded system, the optimal gain is calculated offline and is used by lookup table online, which could reduce the computation time. The results of tests on a practical AGV system demonstrate the effectiveness and accuracy of the strategy presented in this paper.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/01487191
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Supplemental Notes:
- Abstract reprinted with permission of SAE International.
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Authors:
- Jian, Zhang
- Bo, Yang
- Xiaofei, Pei
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Conference:
- SAE 2019 Intelligent and Connected Vehicles Symposium
- Location: Kunshan , China
- Date: 2019-10-15 to 2019-10-16
- Publication Date: 2020-2-24
Language
- English
Media Info
- Media Type: Web
- Features: References;
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Serial:
- SAE Technical Paper
- Publisher: Society of Automotive Engineers (SAE)
- ISSN: 0148-7191
- EISSN: 2688-3627
- Serial URL: http://papers.sae.org/
Subject/Index Terms
- TRT Terms: Algorithms; Automated guided vehicle systems; Automatic controllers; Automatic tracking; Data collection; Steering; Vehicle trajectories
- Subject Areas: Highways; Safety and Human Factors; Vehicles and Equipment;
Filing Info
- Accession Number: 01743530
- Record Type: Publication
- Source Agency: SAE International
- Report/Paper Numbers: 2020-01-5024
- Files: TRIS, SAE
- Created Date: Jun 22 2020 5:53PM