liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
On stability for state-lattice trajectory tracking control
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-1795-5992
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0001-6957-2603
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
2018 (English)In: 2018 Annual American Control Conference (ACC), IEEE, 2018, p. 5868-5875Conference paper, Published paper (Refereed)
Abstract [en]

In order to guarantee that a self-driving vehicle is behaving as expected, stability of the closed-loop system needs to be rigorously analyzed. The key components for the lowest levels of control in self-driving vehicles are the controlled vehicle, the low-level controller and the local planner.The local planner that is considered in this work constructs a feasible trajectory by combining a finite number of precomputed motions. When this local planner is considered, we show that the closed-loop system can be modeled as a nonlinear hybrid system. Based on this, we propose a novel method for analyzing the behavior of the tracking error, how to design the low-level controller and how to potentially impose constraints on the local planner, in order to guarantee that the tracking error is bounded and decays towards zero. The proposed method is applied on a truck and trailer system and the results are illustrated in two simulation examples.

Place, publisher, year, edition, pages
IEEE, 2018. p. 5868-5875
Series
American Control Conference (ACC), E-ISSN 2378-5861
National Category
Control Engineering Robotics
Identifiers
URN: urn:nbn:se:liu:diva-152455DOI: 10.23919/ACC.2018.8430822ISBN: 978-1-5386-5428-6 (electronic)ISBN: 978-1-5386-5427-9 (print)ISBN: 978-1-5386-5429-3 (print)OAI: oai:DiVA.org:liu-152455DiVA, id: diva2:1260273
Conference
2018 Annual American Control Conference (ACC) June 27–29, 2018. Wisconsin Center, Milwaukee, USA
Available from: 2018-11-01 Created: 2018-11-01 Last updated: 2019-01-17
In thesis
1. On motion planning and control for truck and trailer systems
Open this publication in new window or tab >>On motion planning and control for truck and trailer systems
2019 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

During the last decades, improved sensor and hardware technologies as well as new methods and algorithms have made self-driving vehicles a realistic possibility in the near future. Thanks to this technology enhancement, many leading automotive and technology companies have turned their attention towards developing advanced driver assistance systems (ADAS) and self-driving vehicles. Autonomous vehicles are expected to have their first big impact in closed areas, such as mines, harbors and loading/offloading sites. In such areas, the legal requirements are less restrictive and the surrounding environment is more controlled and predictable compared to urban areas. Expected positive outcomes include increased productivity and safety, reduced emissions and the possibility to relieve the human from performing complex or dangerous tasks. Within these sites, different truck and trailer systems are used to transport materials. These systems are composed of several interconnected modules, and are thus large and highly unstable while reversing. This thesis addresses the problem of designing efficient motion planning and feedback control frameworks for such systems.

First, a cascade controller for a reversing truck with a dolly-steered trailer is presented. The unstable modes of the system is stabilized around circular equilibrium configurations using a gain-scheduled linear quadratic (LQ) controller together with a higher-level pure pursuit controller to enable path following of piecewise linear reference paths. The cascade controller is then used within a rapidly-exploring random tree (RRT) framework and the complete motion planning and control framework is demonstrated on a small-scale test vehicle.

Second, a path following controller for a reversing truck with a dolly-steered trailer is proposed for the case when the obtained motion plan is kinematically feasible. The control errors of the system are modeled in terms of their deviation from the nominal path and a stabilizing LQ controller with feedforward action is designed based on the linearization of the control error model. Stability of the closed-loop system is proven by combining global optimization, theory from linear differential inclusions and linear matrix inequality techniques.

Third, a systematic framework is presented for analyzing stability of the closed-loop system consisting of a controlled vehicle and a feedback controller, executing a motion plan computed by a lattice planner. When this motion planner is considered, it is shown that the closed-loop system can be modeled as a nonlinear hybrid system. Based on this, a novel method is presented for analyzing the behavior of the tracking error, how to design the feedback controller and how to potentially impose constraints on the motion planner in order to guarantee that the tracking error is bounded and decays towards zero.

Fourth, a complete motion planning and control solution for a truck with a dolly-steered trailer is presented. A lattice-based motion planner is proposed, where a novel parametrization of the vehicle’s state-space is proposed to improve online planning time. A time-symmetry result is established that enhance the numerical stability of the numerical optimal control solver used for generating the motion primitives. Moreover, a nonlinear observer for state estimation is developed which only utilizes information from sensors that are mounted on the truck, making the system independent of additional trailer sensors. The proposed framework is implemented on a full-scale truck with a dolly-steered trailer and results from a series of field experiments are presented.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2019. p. 78
Series
Linköping Studies in Science and Technology. Licentiate Thesis, ISSN 0280-7971 ; 1832
National Category
Control Engineering Vehicle Engineering Robotics Embedded Systems Computer Engineering
Identifiers
urn:nbn:se:liu:diva-153892 (URN)10.3384/lic-diva-153892 (DOI)9789176851302 (ISBN)
Presentation
2019-01-25, Ada Lovelace, B-building, Campus Valla, 10:15 (English)
Opponent
Supervisors
Available from: 2019-01-17 Created: 2019-01-17 Last updated: 2019-01-22Bibliographically approved

Open Access in DiVA

fulltext(786 kB)61 downloads
File information
File name FULLTEXT03.pdfFile size 786 kBChecksum SHA-512
3aaf487256b1d65f311a31198ec1124f708692fa835bcec2ca0f9775db84c2e88b509b7f2ffae67ae6ee8082701ee4454c3068c29db1229d4371d5d97dcd7942
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Authority records BETA

Ljungqvist, OskarAxehill, DanielLöfberg, Johan

Search in DiVA

By author/editor
Ljungqvist, OskarAxehill, DanielLöfberg, Johan
By organisation
Automatic ControlFaculty of Science & Engineering
Control EngineeringRobotics

Search outside of DiVA

GoogleGoogle Scholar
Total: 64 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 104 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf