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Path following control for a reversing general 2-trailer system
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
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.
2016 (English)In: 2016 IEEE 55TH CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2016, p. 2455-2461Conference paper, Published paper (Refereed)
Abstract [en]

In order to meet the requirements for autonomous systems in real world applications, reliable path following controllers have to be designed to execute planned paths despite the existence of disturbances and model errors. In this paper we propose a Linear Quadratic controller for stabilizing a 2-trailer system with possible off-axle hitching around preplanned paths in backward motion. The controller design is based on a kinematic model of a general 2-trailer system including the possibility for off-axle hitching. Closed-loop stability is proved around a set of paths, typically chosen to represent the possible output from the path planner, using theory from linear differential inclusions. Using convex optimization tools a single quadratic Lyapunov function is computed for the entire set of paths.

Place, publisher, year, edition, pages
IEEE , 2016. p. 2455-2461
Series
IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-138327DOI: 10.1109/CDC.2016.7798630ISI: 000400048102102ISBN: 978-1-5090-1837-6 (print)OAI: oai:DiVA.org:liu-138327DiVA, id: diva2:1109032
Conference
55th IEEE Conference on Decision and Control (CDC)
Available from: 2017-06-13 Created: 2017-06-13 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

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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  • modern-language-association-8th-edition
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