Path tracking control based on tube MPC and time delay motion prediction

Yu, Jiaxing; Guo, Xuexun; Pei, Xiaofei; Chen, Zhenfu; Zhou, Wei; Zhu, Maolin; Wu, Chaoxian

doi:10.1049/iet-its.2019.0088

Cited by 35 publications

(21 citation statements)

References 22 publications

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“…Although the heavy computational load of nonlinear MPC is reduced by online model linearization, the parameter requirements of nonlinear tire dynamics make the model not friendly to various vehicles. Furthermore, a tube model predictive control and time delay motion prediction are combined to deal with signal delay in practice [22]. The concept can be taken as a reference for some delay compensation requirements.…”

Section: Literature Surveymentioning

confidence: 99%

“…Also, since the linear model of the proposed controller is general, so the proposed controller is friendly to various vehicles. Moreover, signal delay in practice [22] is able to be solved in the proposed vehicle controller.…”

Section: Literature Surveymentioning

confidence: 99%

“…The parking-oriented cost function and constraints are designed to overcome the large curvature in parking scenarios. Most of model predictive controllers are designed for on-road scenarios at high speed [16]- [22]. To maintain lateral stability, the limitation of the max steering angle decreases as the increment of vehicle speed [17].…”

Section: Parking-oriented Cost Function and Constraintsmentioning

confidence: 99%

“…1 ≥ 0.5 (22) When it comes to the parking-oriented cost function design, the considerations of state error and control smoothness are taken into account. Moreover, different controls related weighting matrices at curve are designed to overcome the curves with large curvature in parking scenarios.…”

Section: Parking-oriented Cost Function and Constraintsmentioning

confidence: 99%

“…Therefore, the execution time should be compensated for the vehicle controller. To work around this problem, the concept of the time delay motion prediction in [22] is taken as the reference to propose the execution time compensation. Figure 9 shows an example.…”

Section: ) Execution Time Compensationmentioning

confidence: 99%

See 4 more Smart Citations

An Autonomous Parking System of Optimally Integrating Bidirectional Rapidly-Exploring Random Trees and Parking-Oriented Model Predictive Control

Jhang

Lian

2020

IEEE Access

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Autonomous parking techniques can be used to tackle the lacking problem of parking spaces. In this paper, a sampling-based motion planner consisting of optimizing bidirectional rapidly-exploring random trees* (Bi-RRT*) and parking-oriented model predictive control (MPC) is proposed to properly deal with various parking scenarios. The optimal Bi-RRT* approach aims to improve the common defects of traditional sampling-based motion planners, such as uncertainties of path quality and consistency, and exploring inefficiency in narrow spaces. For this reason, the proposed motion planner is able to overcome strict environments with obstacles and narrow spaces. The parking-oriented MPC is then designed for steering and speed controls simultaneously for accurately and smoothly tracking parking paths. Furthermore, the proposed controller is dedicated to work under the practical scenarios, such as vehicle considerations, realtime control, and signal delay. To verify the effects of the proposed autonomous parking system, extensive simulations and experiments are conducted in common and strict parking scenarios, such as perpendicular parking, parallel parking. The simulation results not only verify the effects of each technical element, but also show the capability to deal with the various parking scenarios. Furthermore, various on-car experiments sufficiently demonstrate that the proposed system can be actually implemented in everyday life. INDEX TERMS Autonomous parking system, sampling-based motion planning, parking-oriented vehicle control, bidirectional rapidly-exploring random trees* (Bi-RRT*), model predictive control (MPC), perpendicular parking, parallel parking.

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Section: Literature Surveymentioning

confidence: 99%

Section: Literature Surveymentioning

confidence: 99%

Section: Parking-oriented Cost Function and Constraintsmentioning

confidence: 99%

Section: Parking-oriented Cost Function and Constraintsmentioning

confidence: 99%

Section: ) Execution Time Compensationmentioning

confidence: 99%

See 3 more Smart Citations

An Autonomous Parking System of Optimally Integrating Bidirectional Rapidly-Exploring Random Trees and Parking-Oriented Model Predictive Control

Jhang

Lian

2020

IEEE Access

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Observer‐based path following control for autonomous vehicles with localization errors and tire slip effects

Wang

Zhang

Quan

et al. 2022

Asian Journal of Control

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This paper investigates the problem of path following control for an autonomous vehicle subject to the localization errors and the tire slip effects. First, by analyzing the effects of localization errors, a loss‐of‐effectiveness actuator model is formulated, and a new chain form model is constructed for path following system of the vehicle. Then, the polytopic model is proposed to characterize the nonlinearity of the system, and an observer‐based path following controller is designed by satisfying both the H∞$$ {H}_{\infty } $$ criterion and L1$$ {L}_1 $$ criterion. Finally, the path following controller design problem is converted into an optimization problem, which can be solved readily through convex optimization techniques. The effectiveness of the proposed control strategy is verified by simulation results.

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Design of robust path tracking controller using model predictive control based on steady state input

Kim,

Jeong

2023

J Mech Sci Technol

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Path tracking control based on tube MPC and time delay motion prediction

Cited by 35 publications

References 22 publications

An Autonomous Parking System of Optimally Integrating Bidirectional Rapidly-Exploring Random Trees and Parking-Oriented Model Predictive Control

An Autonomous Parking System of Optimally Integrating Bidirectional Rapidly-Exploring Random Trees and Parking-Oriented Model Predictive Control

Observer‐based path following control for autonomous vehicles with localization errors and tire slip effects

Design of robust path tracking controller using model predictive control based on steady state input

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