Robust Adaptive Safety-Critical Control for Unknown Systems With Finite-Time Elementwise Parameter Estimation

Wang, Shengbo; Lyu, Bo; Wen, Shiping; Shi, Kaibo; Zhu, Song; Huang, Tingwen

doi:10.1109/tsmc.2022.3203176

Cited by 10 publications

(4 citation statements)

References 43 publications

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“…Edge computing helps on-board Artificial Intelligence processing for faster decision making and greater independence. These AI systems have fail-safe mechanisms which hold safety in high regards (Wang, et al, 2023). 2.…”

Section: Concept Of Autonomous Carsmentioning

confidence: 99%

Balancing Safety and Decision-Making Algorithms in AI-Driven Autonomous Vehicles

2024

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Section: Concept Of Autonomous Carsmentioning

confidence: 99%

Balancing Safety and Decision-Making Algorithms in AI-Driven Autonomous Vehicles

2024

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“…Control barrier function (CBF) is an effective way to deal with safety control problem of dynamic systems. 22 CBF combines the state constraints of the system into the controller design, which can ensure the safety of the system. 23 Fruitful results have been achieved in this field.…”

Section: Introductionmentioning

confidence: 99%

CBF‐guided iterative learning control performance optimization for switched systems

Lu,

Qi,

et al. 2024

Intl J Robust & Nonlinear

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This article studies the control barrier function (CBF) guided tracking performance optimization for switched systems under iterative learning control (ILC). CBF is an effective method for handling control system state safety. If the safe set is designed as expected performance, and the unsafe set is not expected, then this may be a good choice for optimizing control system performance. We propose a tracking performance optimization method based on CBF to speed up the convergence of the tracking error. A safe set is used to describe the expected tracking performance, by utilizing CBF, safety is further transformed into a set of inequality conditions that constrain ILC controller gains, which ensures that the tracking error is always within the safe set. In addition, an event‐triggering mechanism (ETM) is considered to reduce unnecessary data transmission, and sufficient conditions for exponential stability of the tracking error of switched systems and ILC controllers design are obtained. Finally, a simulation example is given to verify the feasibility of the proposed method.

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“…To deal with the problem of information safety when information interaction in MASs, many strategies about how to solve the problem of agents have been proposed 37 . These strategies of proposing privacy protection can be divided into three categories.…”

Section: Introductionmentioning

confidence: 99%

“…To deal with the problem of information safety when information interaction in MASs, many strategies about how to solve the problem of agents have been proposed. 37 These strategies of proposing privacy protection can be divided into three categories. The one category is the differential privacy, this approach works by decaying the transmitted information with noise, and the observer then establishes the original information to a pre-specified level of accuracy, 38 the authors proposed a algorithm to achieve minimum privacy breach by adding and subtracting random noises.…”

Section: Introductionmentioning

confidence: 99%

Adaptive containment control of nonlinear multi‐agent systems about privacy preservation with multiple attacks

Gong

Cao

Pan

et al. 2023

Intl J Robust & Nonlinear

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Summary This paper focuses on the problem of adaptive containment control about privacy preservation in nonlinear multi‐agent systems, where followers suffer from multiple cyber‐attacks and leaders have non‐zero control inputs. A multiple attacks mold consisting of denial‐of‐service (DoS) attacks and false data‐injection attacks is constructed for nonlinear systems. The containment control protocol is updated by applying an event‐triggered scheme. This scheme is proposed to dispatch the updating information in the presence of multiple attacks. Meanwhile, to deal with the information insecurity that may exist in the control process, the protocol for privacy preservation about initial information is developed by introducing time‐varying functions as masks. Tracking errors of agents are described by taking the inputs of leaders as the external disturbances. This method does not depend on the widths of boundary layers and reduce the computational complexity. The stability of multi‐agent systems is analyzed by applying the Cauchy inequality, the Young's inequality and the Lyapunov function theory. Finally, two simulation examples are shown to illustrate the effectiveness of the proposed control strategy.

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Robust Adaptive Safety-Critical Control for Unknown Systems With Finite-Time Elementwise Parameter Estimation

Cited by 10 publications

References 43 publications

Balancing Safety and Decision-Making Algorithms in AI-Driven Autonomous Vehicles

Balancing Safety and Decision-Making Algorithms in AI-Driven Autonomous Vehicles

CBF‐guided iterative learning control performance optimization for switched systems

Adaptive containment control of nonlinear multi‐agent systems about privacy preservation with multiple attacks

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