Optimal Connected Cruise Control With Arbitrary Communication Delays

Wang, Zhuwei; Gao, Yu; Fang, Chao; Liu, Lihan; Guo, Song

doi:10.1109/jsyst.2019.2933001

Cited by 26 publications

(9 citation statements)

References 28 publications

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“…Large delays with variations limited in one sampling period. This type of delay can be modelled both as a parametric [32] and norm-bounded [34] uncertainty. 3.…”

Section: Introductionmentioning

confidence: 99%

Discrete‐time modelling methodology of networked control systems under packet delay and dropout

Mohajeri

Madadi

Tavassoli

et al. 2023

IET Cyber-Phy Sys Theory & Ap

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Models and control techniques for networked control systems (NCSs) can be divided into continuous‐time and discrete‐time types. Unlike the continuous‐time analysis, literature on discrete‐time analysis and control of NCSs under packet delay and dropout shows a variety of different models. However, a systematic study of these models is absent in the literature. This article is a methodology for these models. Different factors involved in making this variety are discussed. The models are described and it is shown how they are different or related to each other. The models are from the existing literature. However, to complete the methodology some of the models are introduced by the authors. Furthermore, the concept of sequence matrix is introduced which helps to differentiate some models and should be considered when NCS is analysed as a switched linear system. This methodology can be used as a basis for selecting the suitable model in analysis and design of NCSs. Denial of service (DoS) attack and time delay switch (TDS) attack can be considered as packet dropout and packet delay respectively. Thus, this methodology can also be used in analysis and design of NCS under these cyber‐physical attacks.

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“…Large delays with variations limited in one sampling period. This type of delay can be modelled both as a parametric [32] and norm-bounded [34] uncertainty. 3.…”

Section: Introductionmentioning

confidence: 99%

Discrete‐time modelling methodology of networked control systems under packet delay and dropout

Mohajeri

Madadi

Tavassoli

et al. 2023

IET Cyber-Phy Sys Theory & Ap

View full text Add to dashboard Cite

show abstract

“…First, how to effectively address the influence of network-induced delays on the multi-dimensional formation control of UAVs is a new challenge. Network-induced delays degrade the performance of UAV systems and bring potential drawbacks to the systems’ stability [ 17 , 18 ]. Most existing works focus on stability analysis considering network-induced delays instead of effective control strategy design.…”

Section: Introductionmentioning

confidence: 99%

Optimal UAV Formation Tracking Control with Dynamic Leading Velocity and Network-Induced Delays

Wang

Liu

et al. 2022

Entropy

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With the rapid development of UAV technology, the research of optimal UAV formation tracking has been extensively studied. However, the high maneuverability and dynamic network topology of UAVs make formation tracking control much more difficult. In this paper, considering the highly dynamic features of uncertain time-varying leader velocity and network-induced delays, the optimal formation control algorithms for both near-equilibrium and general dynamic control cases are developed. First, the discrete-time error dynamics of UAV leader–follower models are analyzed. Next, a linear quadratic optimization problem is formulated with the objective of minimizing the errors between the desired and actual states consisting of velocity and position information of the follower. The optimal formation tracking problem of near-equilibrium cases is addressed by using a backward recursion method, and then the results are further extended to the general dynamic case where the leader moves at an uncertain time-varying velocity. Additionally, angle deviations are investigated, and it is proved that the similar state dynamics to the general case can be derived and the principle of control strategy design can be maintained. By using actual real-world data, numerical experiments verify the effectiveness of the proposed optimal UAV formation-tracking algorithm in both near-equilibrium and dynamic control cases in the presence of network-induced delays.

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“…Despite the merits mentioned above, various factors induced by wireless communication such as communication delays and connectivity topologies will cause the significant stability degradation of CCC system, which makes the controller design more challenging [20][21][22]. In [23][24][25], the influence of heterogeneous connectivity topologies on the dynamics of connected automated vehicles is investigated, and analytical conditions for stability are derived.…”

Section: Introductionmentioning

confidence: 99%

Optimal Connected Cruise Control Design with Time‐Varying Leader Velocity and Delays

et al. 2021

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With the development of intelligent transportation system (ITS), owing to its flexible connectivity structures and communication network topologies, connected cruise control (CCC), increasing the situation awareness of the autonomous vehicle without redesigning the other vehicles, is an advanced cruise control technology attracted extensive attention. However, due to the uncertain traffic environment and the movement of the connected vehicles, the leader speed is typically highly dynamic. In this paper, taking the uncertain time-varying leading vehicle velocity and communication delays into consideration, an optimal CCC algorithm is proposed for both near-static case and general dynamic control cases. First, the analysis for discrete-time error dynamics model of the longitudinal vehicle platoon is performed. Then, in order to minimize the error between the desired and actual states, a linear quadratic optimization problem is formulated. Subsequently, in near-static control case, an efficient algorithm is proposed to derive the solution of the optimization problem by two steps. Specifically, the online step calculates the optimal control scheme according to the current states and previous control signals, and the off-line step calculates the corresponding control gain through backward recursion. Then, the results are further extended to the general dynamic control case where the leader vehicle moves at an uncertain time-varying velocity. Finally, simulation results verify the effectiveness of the proposed CCC algorithm.

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Optimal Connected Cruise Control With Arbitrary Communication Delays

Cited by 26 publications

References 28 publications

Discrete‐time modelling methodology of networked control systems under packet delay and dropout

Discrete‐time modelling methodology of networked control systems under packet delay and dropout

Optimal UAV Formation Tracking Control with Dynamic Leading Velocity and Network-Induced Delays

Optimal Connected Cruise Control Design with Time‐Varying Leader Velocity and Delays

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