Tube-Based Discrete Controller Design for Vehicle Platoons Subject to Disturbances and Saturation Constraints

Cooperative adaptive cruise control (CACC) is a promising intelligent vehicle technology for improving traffic flow stability, throughput, and safety. One major control objective of CACC is to guarantee \mathcal {L}_{p} string stability, i.e., \mathcal {L}_{p} -norm measured disturbance is unifor...

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Veröffentlicht in:IEEE transactions on control systems technology 2020-05, Vol.28 (3), p.1066-1073
Hauptverfasser: Feng, Shuo, Sun, Haowei, Zhang, Yi, Zheng, Jianfeng, Liu, Henry X., Li, Li
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container_issue 3
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creator Feng, Shuo
Sun, Haowei
Zhang, Yi
Zheng, Jianfeng
Liu, Henry X.
Li, Li
description Cooperative adaptive cruise control (CACC) is a promising intelligent vehicle technology for improving traffic flow stability, throughput, and safety. One major control objective of CACC is to guarantee \mathcal {L}_{p} string stability, i.e., \mathcal {L}_{p} -norm measured disturbance is uniformly bounded along the vehicle string. Most existing methods for string stability are laborious for implementation without considering either heterogeneous disturbances (e.g., tracking errors and unmodeled dynamics) or saturation constraints (e.g., input saturation). The decentralized model predictive control (MPC) method, which is a widely used feedforward control for string stability, suffers the burdens of computation cost and intervehicular communication. To fill these gaps, we distinguish different types of disturbances and use different ways to handle them. We use feedforward control for large yet infrequent disturbances and feedback control for small yet frequent disturbances. Different from MPC, our feedforward control is event-triggered so that the intervehicle communication and planning costs can be significantly reduced. Different from pure robust feedback control, our combination of feedback and feedforward control could reduce the conservation of the controller. Theoretical analysis and simulations show that the proposed method guarantees \mathcal {L}_{p} string stability of vehicle platoons considering heterogeneous disturbances and saturation constraints.
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One major control objective of CACC is to guarantee <inline-formula> <tex-math notation="LaTeX">\mathcal {L}_{p} </tex-math></inline-formula> string stability, i.e., <inline-formula> <tex-math notation="LaTeX">\mathcal {L}_{p} </tex-math></inline-formula>-norm measured disturbance is uniformly bounded along the vehicle string. Most existing methods for string stability are laborious for implementation without considering either heterogeneous disturbances (e.g., tracking errors and unmodeled dynamics) or saturation constraints (e.g., input saturation). The decentralized model predictive control (MPC) method, which is a widely used feedforward control for string stability, suffers the burdens of computation cost and intervehicular communication. To fill these gaps, we distinguish different types of disturbances and use different ways to handle them. We use feedforward control for large yet infrequent disturbances and feedback control for small yet frequent disturbances. Different from MPC, our feedforward control is event-triggered so that the intervehicle communication and planning costs can be significantly reduced. Different from pure robust feedback control, our combination of feedback and feedforward control could reduce the conservation of the controller. 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Different from MPC, our feedforward control is event-triggered so that the intervehicle communication and planning costs can be significantly reduced. Different from pure robust feedback control, our combination of feedback and feedforward control could reduce the conservation of the controller. 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One major control objective of CACC is to guarantee <inline-formula> <tex-math notation="LaTeX">\mathcal {L}_{p} </tex-math></inline-formula> string stability, i.e., <inline-formula> <tex-math notation="LaTeX">\mathcal {L}_{p} </tex-math></inline-formula>-norm measured disturbance is uniformly bounded along the vehicle string. Most existing methods for string stability are laborious for implementation without considering either heterogeneous disturbances (e.g., tracking errors and unmodeled dynamics) or saturation constraints (e.g., input saturation). The decentralized model predictive control (MPC) method, which is a widely used feedforward control for string stability, suffers the burdens of computation cost and intervehicular communication. To fill these gaps, we distinguish different types of disturbances and use different ways to handle them. We use feedforward control for large yet infrequent disturbances and feedback control for small yet frequent disturbances. Different from MPC, our feedforward control is event-triggered so that the intervehicle communication and planning costs can be significantly reduced. Different from pure robust feedback control, our combination of feedback and feedforward control could reduce the conservation of the controller. Theoretical analysis and simulations show that the proposed method guarantees <inline-formula> <tex-math notation="LaTeX">\mathcal {L}_{p} </tex-math></inline-formula> string stability of vehicle platoons considering heterogeneous disturbances and saturation constraints.]]></abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TCST.2019.2896539</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-2117-4427</orcidid><orcidid>https://orcid.org/0000-0001-5526-866X</orcidid><orcidid>https://orcid.org/0000-0002-9428-1960</orcidid><orcidid>https://orcid.org/0000-0002-3685-9920</orcidid></addata></record>
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subjects Adaptive control
Computer simulation
Control stability
Control systems design
Control theory
Controllers
Cooperative adaptive cruise control (CACC)
Cooperative control
Cruise control
disturbance <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">Lₚ string stability (DSS)
Disturbances
Electron tubes
Feedback control
Feedforward control
Feedforward systems
Flow stability
Intelligent vehicles
Mathematical model
model predictive control
Predictive control
Robust control
Saturation
Stability criteria
Strings
Tracking errors
Traffic flow
Traffic safety
tube
Vehicle dynamics
title Tube-Based Discrete Controller Design for Vehicle Platoons Subject to Disturbances and Saturation Constraints
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