A Novel EPT Autonomous Motion Control Framework for an Off-Axle Hitching Tractor-Trailer System With Drawbar

Liu, Jie; Dong, Xianzhou; Wang, Junyu; Lu, Chen; Zhao, Xudong; Wang, Xinwei

doi:10.1109/tiv.2020.3033115

Cited by 18 publications

(11 citation statements)

References 28 publications

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“…It is a natural idea to find a coarse path/trajectory via sampling and search to identify the homotopy class, and then use it to warm-start the numerical OCP solution process. Liu et al [4] searched for collision-free waypoints and then connected Reeds-Shepp primitives between adjacent waypoints to form an initial guess for numerical OCP. Bergman et al [20] divided a searched path into segments and solved several subtle OCPs with the two-point boundary conditions of each segment.…”

Section: A Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Optimization-Based Maneuver Planning for a Tractor-Trailer Vehicle in a Curvy Tunnel: A Weak Reliance on Sampling and Search

Acarman

et al. 2022

IEEE Robot. Autom. Lett.

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This study is focused on the maneuver planning problem for a tractor-trailer vehicle in a curvy and tiny tunnel. Due to the curse of dimensionality, the prevalent sampling-andsearch-based planners used to handle a rigid-body vehicle well become less efficient when the trailer number grows or when the tunnel narrows. This fact also has impacts on an optimizationbased planner if it counts on a sampling-and-search-based initial guess to warm-start. We propose an optimization-based maneuver planner that weakly relies on the sampling and search, hoping to get rid of the curse of dimensionality and thus find optima rapidly. The proposed planner comprises three stages: stage 1 identifies the homotopy class via A* search in a 2D grid map; stage 2 recovers the kinematic feasibility with softened intermediate problems iteratively solved; stage 3 finds an optimum that strictly satisfies the nominal collision-avoidance constraints. Optimization-based planners are commonly known to run slowly, but this work shows that they have obvious advantages over the prevalent sampling-and-search-based planners when the solution space dimension is high and/or the constraints are harsh.

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Section: A Related Workmentioning

confidence: 99%

“…A tractor-trailer vehicle sweeps a smaller area than the same-length rigid-body vehicle when turning around [2,3]. This property enables its agile movement in tiny environments, thus yielding wide applications in agriculture, logistics, and military [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Optimization-Based Maneuver Planning for a Tractor-Trailer Vehicle in a Curvy Tunnel: A Weak Reliance on Sampling and Search

Acarman

et al. 2022

IEEE Robot. Autom. Lett.

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“…To this end, the dynamic models of tractor-trailers have been developed to design tracking controllers to cope with inertial, Coriolis, centripetal, damping and gravity forces, and torques acting on the vehicle. [18][19][20][21][22][23][24][25][26][27] For the example, robust nonlinear controllers are presented for the trajectory tracking control of TTWMRs in Alipour et al 18 and Khalaji and Moosavian. 19 A PID-based controller is developed for the target-tracking problem of a tractor-trailer mobile robot in Khalaji.…”

Section: Background and Related Workmentioning

confidence: 99%

“…20 A full-state trajectory tracking controller is designed for the tractor towing a trailer in Kassaeiyan et al 21 Recently, novel motion controllers have been developed for the tractor-trailers in the literature for agricultural and industrial applications. [22][23][24][25] However, most of the available results are focused on a tractor with a singletrailer. To increase the transportation capacity, it is of interest to extend the connected trailers chain up to n-trailers.…”

Section: Background and Related Workmentioning

confidence: 99%

Input-output feedback linearization control of a tractor with n-trailers mechanism considering the path curvature

Shojaei

Taghavifar

2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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In this paper, an observer-based proportional-integral-derivative (PID) controller is proposed for an autonomous tractor with n-trailer units with prescribed transient and steady-state performances by compensating the negative effect of the path curvature during the turning of the trailers. The control objective is to place the position of the last trailer on a desired trajectory without any deviation in the course of its turning. Since the curvature of the trajectory causes a remarkable unwanted deviation of the trailers’ positions from the path, an input-output model is derived for the tractor with n-trailers based on the extended look-ahead control concept which employs a corrective angle to compensate the path curvature. A nonlinear transformation is employed to transform constrained errors into unconstrained ones and to obtain an open-loop error dynamic model in terms of the unconstrained errors. Then, a neural network adaptive PID output-feedback linearization-based controller is proposed to force the tracking errors to the zero neighbourhood with a guaranteed prescribed performance with preferable overshoot/undershoot, convergence speed and final tracking accuracy. The Kalman–Yakobovich (KY) lemma is employed to prove the closed-loop stability of the observer-controller system strongly. Numerical simulations are given to show the controller’s effectiveness in practice.

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“…Due to the benefit of symplectic-conserved property and local pseudospectral discretization, SPMs are of high efficiency and precision. More recently, taking the SPM as the internal solver, a fast MPC algorithm is developed (Wang et al, 2019) and successfully applied to trajectory tracking for various mechanical systems (Liu et al, 2019a; Liu et al, 2019b; Liu et al, 2020; Wang et al, 2020a; Wang et al, 2020c), further demonstrating its good robustness and online computational efficiency. Hence, it seems appealing to develop fast MHE algorithms by incorporating the SPM.…”

Section: Introductionmentioning

confidence: 99%

A fast-moving horizon estimation method based on the symplectic pseudospectral algorithm

Wang

Liu

Peng

et al. 2021

Transactions of the Institute of Measurement and Control

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In this paper, a fast-moving horizon state estimation algorithm for nonlinear continuous systems with measurement noises and model disturbances is developed. The optimization problem required to be solved at each sampling instant is formulated into a backward nonlinear optimal control problem over the finite past. Once prior knowledge of the observed system is available, constraints can be further imposed. The highly efficient and accurate symplectic pseudospectral algorithm is taken as the core solver, which leads to the symplectic pseudospectral moving horizon estimation (SP-MHE) method. The developed SP-MHE is first evaluated by numerical simulations for a hovercraft. Then the developed method is extended to parameter estimation and applied to a chaotic system with an unknown parameter. Simulation results show that the SP-MHE can generate accurate estimations even under large sampling periods or large noise where regular filters fail. In addition, the SP-MHE exhibits excellent online efficiency, suggesting it can be used for scenarios where the sampling period is relatively small.

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A Novel EPT Autonomous Motion Control Framework for an Off-Axle Hitching Tractor-Trailer System With Drawbar

Cited by 18 publications

References 28 publications

Optimization-Based Maneuver Planning for a Tractor-Trailer Vehicle in a Curvy Tunnel: A Weak Reliance on Sampling and Search

Optimization-Based Maneuver Planning for a Tractor-Trailer Vehicle in a Curvy Tunnel: A Weak Reliance on Sampling and Search

Input-output feedback linearization control of a tractor with n-trailers mechanism considering the path curvature

A fast-moving horizon estimation method based on the symplectic pseudospectral algorithm

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