Research Papers

Composite Path Tracking Control for Tractor–Trailer Vehicles Via Constrained Model Predictive Control and Direct Adaptive Fuzzy Techniques

[+] Author and Article Information
Ming Yue

School of Automotive Engineering,
Dalian University of Technology,
Dalian 116024, Liaoning, China
e-mail: yueming@dlut.edu.cn

Xiaoqiang Hou, Wenbin Hou

School of Automotive Engineering,
Dalian University of Technology,
Dalian 116024, Liaoning, China

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received September 17, 2016; final manuscript received May 13, 2017; published online July 28, 2017. Editor: Joseph Beaman.

J. Dyn. Sys., Meas., Control 139(11), 111008 (Jul 28, 2017) (12 pages) Paper No: DS-16-1446; doi: 10.1115/1.4036884 History: Received September 17, 2016; Revised May 13, 2017

Tractor–trailer vehicles will suffer from nonholonomic constraint, uncertain disturbance, and various physical limits, when they perform path tracking maneuver autonomously. This paper presents a composite path tracking control strategy to tackle the various problems arising from not only vehicle kinematic but also dynamic levels via two powerful control techniques. The proposed composite control structure consists of a model predictive control (MPC)-based posture controller and a direct adaptive fuzzy-based dynamic controller, respectively. The former posture controller can make the underactuated trailer midpoint follow an arbitrary reference trajectory given by the earth-fixed frame, as well as satisfying various physical limits. Meanwhile, the latter dynamic controller enables the vehicle velocities to track the desired velocities produced by the former one, and the global asymptotical convergence of dynamic controller is strictly guaranteed in the sense of Lyapunov stability theorem. The simulation results illustrate that the presented control strategy can achieve a coordinated control effect for the sophisticated tractor–trailer vehicles, thereby enhancing their movement performance in complex environments.

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Fig. 2

Schematic diagram of the direct adaptive fuzzy control system

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Fig. 1

Schematic diagram of tractor–trailer vehicle system

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Fig. 3

Time responses of trajectory tracking for the tractor–trailer vehicle

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Fig. 4

Structure of an adaptive fuzzy logic system

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Fig. 5

Tracking errors for state variables

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Fig. 6

ex,ey,andeφ in three-dimensional (3D) space

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Fig. 7

ex, ey, and eθ in 3D space

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Fig. 8

Time response of linear velocity tracking

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Fig. 9

Time response of angular velocity tracking

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Fig. 10

Actual and desired hitch angle for tractor–trailer vehicle

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Fig. 11

Control inputs for tractor–trailer vehicle




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