Fault-tolerant human-machine shared scheme for collision avoidance of intelligent vehicles considering driver error and actuator fault

Yan, Mingyue; Chen, Wuwei; Wang, Qidong; Zhao, Lian; Cai, Bixin; Liu, Shengshan

doi:10.1080/00423114.2022.2142616

Cited by 2 publications

(5 citation statements)

References 68 publications

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“…The proposed algorithm is designed based on the concept of state optimization. Specifically, in the constructed system (11), the calculation of the system discrete state variables x k depends on the onboard sensors, such as the IMU and positioning sensors, which precisely measure the position, speed, and yaw of the intelligent vehicle. Under this premise, the stability and accuracy of the control process are ensured.…”

Section: Design Of Model Predictive Controller Based On Ddobmentioning

confidence: 99%

“…(1) The constrained optimization problem (17) has a solution at k = 0. (2) Based on system (11), for the nominal system without considering external disturbances and model uncertainties, as shown in equation ( 45):…”

Section: Stability Analysis Of the Closed-loop Systemmentioning

confidence: 99%

“…The prediction horizon is N p , the control horizon is N c , and (11) is iteratively computed to obtain the sequence of state variables of the system in predicted horizon N p as:…”

Section: Design Of Model Predictive Controller Based On Ddobmentioning

confidence: 99%

“…The effective path tracking performance can be obtained by these methods when the intelligent vehicle is in an ideal state and there are no unknown parameter fluctuations or external disturbances. However, multi-channel uncertain disturbances such as model parameter fluctuations [6,7], external unmodeled dynamics [8,9] and actuator response lag or even faults [10,11] are the key challenges faced by the path tracking of intelligent vehicles in real environment, which will affect the accuracy and stability of the path tracking. Therefore, considering multi-channel uncertain disturbances is necessary to further improve the comprehensive performance of path tracking.…”

Section: Introductionmentioning

confidence: 99%

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Model predictive path tracking control of intelligent vehicles based on dual-stage disturbance observer under multi-channel disturbances

Guo,

Guan

et al. 2024

Meas. Sci. Technol.

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Parameter fluctuations, unmodeled dynamics, speed variation, steering actuator faults, and other multi-channel uncertain disturbances are the key challenges faced by the path tracking control of intelligent vehicles, which will affect the accuracy and stability of the path tracking. Therefore, a model predictive control (MPC) method based on a dual-stage disturbance observer (DDOB) is proposed in this paper. First, a tracking error dynamics model considering multi-channel uncertain disturbances is constructed, based on which a model predictive controller is designed to obtain the nominal front wheel steering angle by the Karush-Kuhn-Tucker (KKT) condition. Furthermore, the dual-stage disturbance observer is designed to enable real-time estimation of the system disturbances, and then the estimated disturbances are used as the compensation for the nominal front wheel steering angle, which establishes the MPC control law with parallel compensation of the dual-stage disturbance observer. Finally, the error boundedness of the dual-stage disturbance observer and the global stability of the model predictive controller are analyzed. The effectiveness and superiority of the proposed algorithm are verified through Carsim-Simulink simulation and hardware-in-the-loop (HiL) experiments.

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Section: Design Of Model Predictive Controller Based On Ddobmentioning

confidence: 99%

Section: Stability Analysis Of the Closed-loop Systemmentioning

confidence: 99%

“…The prediction horizon is N p , the control horizon is N c , and (11) is iteratively computed to obtain the sequence of state variables of the system in predicted horizon N p as:…”

Section: Design Of Model Predictive Controller Based On Ddobmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Model predictive path tracking control of intelligent vehicles based on dual-stage disturbance observer under multi-channel disturbances

Guo,

Guan

et al. 2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

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“…So, it has the advantage of being easy to implement [23] and is more suitable for practical systems [24,25]. When sensors or actuators of a vehicle fail, fault-tolerant control is critical to ensure the vehicle's stability and safety [26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Research on Path Tracking Fault-Tolerant Control Strategy for Intelligent Commercial Vehicles Based on Brake Actuator Failure

Cui,

Bao,

Guo

et al. 2024

Actuators

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With the development of safety technologies for intelligent commercial vehicles, electronic pneumatic braking systems (EBSs) have been widely used. However, EBS actuators may fail during vehicle operation and thus create safety problems. For this reason, we propose a path-tracking fault-tolerant control strategy under EBS actuator failure in intelligent commercial vehicles. First, in order to be able to characterize different types of brake actuator faults during the EBS differential braking process of a vehicle, a comprehensive fault coefficient for calculating the degree of fault is designed, and a BES generalized fault model is established. Second, the faults are introduced into the fault-tolerant controller through the comprehensive fault coefficients for braking torque calculation and braking pressure allocation. Thus, a vehicle path model with the complete fault coefficients as variable parameters is established. Then, based on the LPV system gain scheduling, a path-tracking LPV/H∞ fault-tolerant controller under EBS actuator faults in commercial vehicles is designed, which is used to solve the safety problem arising from sudden EBS actuator faults. Finally, we conducted experimental validation through hardware-in-the-loop tests. The results demonstrate that the control strategy designed in this paper redistributes the braking torque and synergizes with the steering system to enhance vehicle stability, thereby improving vehicle safety in the EBS failure mode.

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Fault-tolerant human-machine shared scheme for collision avoidance of intelligent vehicles considering driver error and actuator fault

Cited by 2 publications

References 68 publications

Model predictive path tracking control of intelligent vehicles based on dual-stage disturbance observer under multi-channel disturbances

Model predictive path tracking control of intelligent vehicles based on dual-stage disturbance observer under multi-channel disturbances

Research on Path Tracking Fault-Tolerant Control Strategy for Intelligent Commercial Vehicles Based on Brake Actuator Failure

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