Linear quadratic regulator based on extended state observer–based active disturbance rejection control of autonomous vehicle path following control

Kang, Nan; Yong, Han; Wang, Biyao; Guan, Tian; Feng, Wenhan

doi:10.1177/09596518221118028

Proceedings of the Institution of Mechanical Engineers, Part I:

2022

DOI: 10.1177/09596518221118028

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Linear quadratic regulator based on extended state observer–based active disturbance rejection control of autonomous vehicle path following control

Nan Kang

Han Yong

Biyao Wang

et al.

Abstract: This article studies the control problem of autonomous vehicle path following with coordination of active front steering and differential steering. A hierarchical control scheme including upper layer and lower layer is proposed. In the upper layer controller, a linear quadratic regulator based on extended state observer is proposed to generate the front-wheel steering angle and external yaw moment, where extended state observer is used to estimate and compensate for the system uncertainty and external disturba… Show more

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2024

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Cited by 4 publications

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Adaptive model predictive control–based curved path-tracking strategy for autonomous vehicles under variable velocity

Zhang,

Kong,

Liu

et al. 2024

Transactions of the Institute of Measurement and Control

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Maintaining the curved path-tracking accuracy and stability of autonomous vehicles under various road conditions is a significant challenge in the field of vehicle control. To address this limitation, a curved path-tracking strategy under variable velocity based on the adaptive model predictive control (MPC) is proposed for autonomous vehicles. Through the analysis of the vehicle dynamics model, the theoretical basis is presented to improve the performance of the curved path tracking by changing the vehicle velocity, and the adaptive velocity (AV) planner is designed to generate variable velocities depending on the path curvature and road friction coefficients. In addition, the adaptive model predictive controller, which adopts the fuzzy inference system with vehicle velocity and path curvature as inputs to obtain the adaptive prediction horizon (APH), is employed to realize curved path-tracking and velocity control with actuator constraints by manipulating the steering angle of the front wheels and the longitudinal tire forces of the vehicle. In comparison with the control strategy with three other control strategies based on MPC algorithm via simulation experiments on the Simulink/CarSim platform, the curved path-tracking control strategy with AV and APH proposed in this paper exhibits satisfactory performance in terms of path-tracking accuracy and stability.

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Adaptive model predictive control–based curved path-tracking strategy for autonomous vehicles under variable velocity

Zhang,

Kong,

Liu

et al. 2024

Transactions of the Institute of Measurement and Control

View full text Add to dashboard Cite

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Robust integrated control of autonomous vehicles path following with response performance improvement considering lateral stability

Kang,

Tang,

Han

2024

Proceedings of the Institution of Mechanical Engineers, Part D:

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In this paper, a robust integrated control scheme is developed for autonomous vehicles path following considering both yaw stability and roll stability. First, a controller with H∞ and optimal guaranteed cost performances is presented, and the poles of the closed-loop system are configured in a given disk region to improve the state response performance. The controller outputs front and rear wheel angles for path following, as well as an external yaw moment and an external roll moment for lateral stability control. Secondly, the braking forces acted on four wheels are optimally distributed by means of quadratic programing. Besides, the steering angles of the four wheels conform to the Ackermann geometry relation. Finally, the proposed control scheme is verified by CarSim/Simulink co-simulation, the results show that the scheme has better performance on path following accuracy and stability of yaw and roll. Meanwhile, constraining the poles in a given disk region can improve the state response performance of the vehicle during operation.

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Fault-tolerant control of the main drive system of rolling mill based on fault reconfiguration

Zhang,

Li,

Liang

2024

Proceedings of the Institution of Mechanical Engineers, Part I:

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A mathematical model of the main drive system of rolling mill is developed for the motor armature faults in the main drive system of rolling mill, taking into account the effects of nonlinear damping, friction damping between rolls and external perturbations on the system during operation. The unknown input observer is designed to process perturbations and errors as unknown inputs, and the [Formula: see text] performance index is designed to improve the robustness of the unknown input observer to fault reconfiguration. At the same time, in order to ensure the stability of the main drive system of rolling mill after the occurrence of faults, an active fault-tolerant controller is designed for the main drive system of rolling mill after obtaining the accurate fault reconfiguration value, which realizes the active fault-tolerant control of the main drive system of rolling mill. Through the simulation study on the main drive system of 2030 mm cold rolling mill stand F4, it is shown that the system is restored to the normal state after adding the fault-tolerant controller, and the motor angular speed error and roll angular speed error are 2.12% and 2.43%, respectively. Comparing with the fault-tolerant control method based on fault estimation, the root-mean-square errors of the motor angular speed and roll angular speed estimates of the designed fault-tolerant control method are reduced by 4.24% and 3.28%, respectively. Simulation verifies the effectiveness of the proposed method.

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Linear quadratic regulator based on extended state observer–based active disturbance rejection control of autonomous vehicle path following control

Cited by 4 publications

References 38 publications

Adaptive model predictive control–based curved path-tracking strategy for autonomous vehicles under variable velocity

Adaptive model predictive control–based curved path-tracking strategy for autonomous vehicles under variable velocity

Robust integrated control of autonomous vehicles path following with response performance improvement considering lateral stability

Fault-tolerant control of the main drive system of rolling mill based on fault reconfiguration

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