Robust path-following control for articulated heavy-duty vehicles

Barbosa, Filipe Marques; Marcos, Lucas B.; Silva, Maíra Martins da; Terra, Marco H.; Grassi, Valdir

doi:10.1016/j.conengprac.2019.01.017

Cited by 44 publications

(24 citation statements)

References 22 publications

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“…The robust path tracking control method based on fuzzy disturbance observer is studied, and the stability of the system without disturbance is analyzed based on Lyaprov method [133][134][135]. Filipe Marques Barbosa et al proposed a path tracking control strategy based on robust linear quadratic programming optimization control for autonomous heavy truck vehicle to deal with uncertain load, and established a robust linear quadratic programming performance function with penalty coefficients [136]. Amir Benloucif et al established a vehicle dynamics model based on the T-S fuzzy model for vehicle obstacle avoidance control, and proposed LMI steering control method based on the T-S fuzzy model [137].…”

Section: Other Robust Control Methodsmentioning

confidence: 99%

Control Strategies on Path Tracking for Autonomous Vehicle: State of the Art and Future Challenges

Yao

Tian

Wang³

et al. 2020

IEEE Access

123

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Autonomous vehicle technology aims to improve driving safety, driving comfort, and its economy, as well as reduce traffic accident rate. As the basic part of autonomous vehicle motion control module, path tracking aims to follow the reference path accurately, ensure vehicle stability and satisfy the robust performance of the control system. This paper introduces the representative control strategies, robust control strategies and parameter observation-based control strategies on path tracking for autonomous vehicle. Furthermore, the implementations and disadvantages are summarized. Most importantly, the critical review in this paper provides a list and discussion of the remaining challenges and unsolved problems on path tracking control.

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Section: Other Robust Control Methodsmentioning

confidence: 99%

Control Strategies on Path Tracking for Autonomous Vehicle: State of the Art and Future Challenges

Yao

Tian

Wang³

et al. 2020

IEEE Access

123

View full text Add to dashboard Cite

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“…In conclusion, many active steering controllers including LQR, SMC and H 1 , which mainly concentrated on either [15,20,[23][24][25] or both [21,22] of the low-speed path following and high-speed lateral stabilities, have been proposed for the AHVs, especially for the tractor/ semi-trailer. However, only a few controllers can simultaneously ensure low-speed path tracking and high-speed lateral stabilities and the focus previewer controller was never used in these studies.…”

Section: Introductionmentioning

confidence: 99%

Active steering control based on preview theory for articulated heavy vehicles

et al. 2021

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This paper investigates the active steering control of the tractor and the trailer for the articulated heavy vehicle (AHV) to improve its high-speed lateral stability and low-speed path following. The four-degree-of-freedom (4-DOF) single track dynamic model of the AHV with a front-wheel steered trailer is established. Considering that the road information at the driver’s focus is the most clear and those away from the focus blurred, a new kind controller based on the fractional calculus, i.e., a focus preview controller is designed to provide the steering input for the tractor to make it travel along the desired path. In addition, the active steering controllers based on the linear quadratic regulator (LQR) and single-point preview controller respectively are also proposed for the trailer. However, the latter is designed on the basis of the articulation angle between the tractor and trailer, inspired by the idea of the driver’s single-point preview controller. Finally, the single lane change maneuver and 90o turn maneuver are carried out. And the simulation results show that compared with the single-point preview controller, the new kind preview controller for the tractor can have good high speed maneuvering stability and low speed path tracking ability by adjusting the fractional order of the controller. On this basis, three different AHVs with the same tractor are simulated and the simulation results show that the AHV whose trailer adopts the single-point preview controller has better high-speed lateral stability and low-speed path tracking than the AHV whose trailer adopts the LQR controller.

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“…27 There are similar robust control methods in the literature being reported which are associated to the techniques to withstand the effect of external disturbances or parametric uncertainties arising from the system dynamics such that the vehicle lateral dynamics stability and path-tracking performance is guaranteed. [29][30][31][32][33] However, most of these studies are viewed from a Lyapunov perspective while there are alternative methods which are suggestive of a more systematic design strategy with more explicit perspectives of the controller inputs to withstand the effect of parametric uncertainties such as Immersion and Invariance principle. 34 In Guo et al, 35 the MPC is designed for path following problem and it is experimentally verified on the Hongqi autonomous car.…”

Section: Introductionmentioning

confidence: 99%

A novel adaptive control approach for path tracking control of autonomous vehicles subject to uncertain dynamics

Mohammadzadeh

Taghavifar

2020

Proceedings of the Institution of Mechanical Engineers, Part D:

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Autonomous ground vehicles are constantly exposed to matched/mismatched uncertainties and disturbances and different operating conditions. Consequently, robustness to resist the undesirable effect of changes in the nominal parameters of the vehicle is a significant provision for satisfactory path-tracking control of these vehicles. The accomplishment of lateral path-tracking control is an essential task expectable from autonomous ground vehicles, particularly during critical maneuvers, abrupt cornering, and lane changes at high speeds. This paper presents a new control approach based on immersion and invariance control theorem. The asymptotic stability of the proposed method is ensured and the adaptation laws for the parameters are derived based on the I&I stability theorem. The effectiveness of the proposed control method is confirmed for autonomous ground vehicles systems while making a double-lane-change at various forward speeds. The robustness of the proposed control method is evaluated under parametric uncertainties related to the autonomous ground vehicle and different road conditions. The obtained results suggest that the proposed control method holds the capacity to be applied effectively to the path-tracking task of autonomous ground vehicles under a broad range of operating conditions, parametric uncertainness, and external disturbances.

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Robust path-following control for articulated heavy-duty vehicles

Cited by 44 publications

References 22 publications

Control Strategies on Path Tracking for Autonomous Vehicle: State of the Art and Future Challenges

Control Strategies on Path Tracking for Autonomous Vehicle: State of the Art and Future Challenges

Active steering control based on preview theory for articulated heavy vehicles

A novel adaptive control approach for path tracking control of autonomous vehicles subject to uncertain dynamics

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