Formation Control of Wheeled Mobile Robots With Multiple Virtual Leaders Under Communication Failures

Wu, Yanhong; Zuo, Zhiqiang; Han, Qiaoni; Wang, Yijing; Yang, Hongjiu

doi:10.1109/tcst.2022.3175315

Cited by 11 publications

(5 citation statements)

References 38 publications

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“…2-3. The parameter estimation error cannot reach zero since a small constant contained in the right-hand side of (24), which is plotted in Fig. 4.…”

Section: Case 1) No Fdi Attacks On the Control Inputsmentioning

confidence: 99%

“…In the light of ( 16) and (24), the stability analysis results are supported, more specifically, the closed-loop error systems are globally ultimately uniformly stable, implies that the relative position and velocity errors given in (12) are driven to a compact set containing a small radius, while 𝜃 ̂(t) cannot be guaranteed to converge to θ(t) due to the term of square of θ(t) − 𝜃 ̂(t) are not concluded in (24). This concludes the proof.…”

Section: Theoremmentioning

confidence: 99%

“…In [23], the cooperative problem of multirobot systems in the presence of stochastic perturbations was considered, and a decentralized formation control method was proposed. Formation of multiagent systems subject to communication failures is discussed in [24]. To overcome the deception attacks, a distributed resilient control method is designed to cope with the formation problem of multiagent systems [25].…”

mentioning

confidence: 99%

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Adaptive Learning Gain based Resilient Control of Multiagent Systems with Partial Uncertain Control Coefficients Under FDI Attacks

Yang,

Long,

Lei

2023

Preprint

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This paper presents a novel approach to security resilient control in collective multiagent systems, incorporating an adaptive learning gain mechanism. The proposed method addresses challenges posed by bounded external disturbances, partial false-data-injection (FDI) attacks on the actuators, and partial unknown time-varying control coefficients. The presented synthesized control consists of following parts. Specifically, a robust adaptive control law with implicit learning is proposed to address the modeling parameterized uncertainties and disturbances. An adaptive learning gain-based control technique is designed to reduce the adversarial effect caused by mismatched disturbances with time-varying parameters, which curbs the cooperative errors to the assigned field. A resilient control approach is established to mitigate the detrimental impact of malicious attacks on actuators. An adaptive control strategy, utilizing a novel congelation of variables, is implemented to address the control issue pertaining to partially unknown control coefficients. This technique ensures that control inputs align with the practical actuators by establishing feasible control bounds. The property of the resulting closed-loop error multiagent systems is analyzed. Finally, the efficacy of the designed controller is illustrated by providing an illustrative example.

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“…2-3. The parameter estimation error cannot reach zero since a small constant contained in the right-hand side of (24), which is plotted in Fig. 4.…”

Section: Case 1) No Fdi Attacks On the Control Inputsmentioning

confidence: 99%

Section: Theoremmentioning

confidence: 99%

mentioning

confidence: 99%

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Adaptive Learning Gain based Resilient Control of Multiagent Systems with Partial Uncertain Control Coefficients Under FDI Attacks

Yang,

Long,

Lei

2023

Preprint

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“…Widespread disturbance and uncertainties will influence the motion control performance of a wheeled mobile robot. The disturbance resistance is a central issue of the motion control of the WMR, such as trajectory tracking, 1 path following, 2 and formation control 3,4 . The main methods are divided into two kinds, such as disturbance attenuation, and disturbance rejection control.…”

Section: Introductionmentioning

confidence: 99%

“…The disturbance resistance is a central issue of the motion control of the WMR, such as trajectory tracking, 1 path following, 2 and formation control. 3,4 The main methods are divided into two kinds, such as disturbance attenuation, and disturbance rejection control. The robust control and adaptive control belong to the first kind 5 ).…”

mentioning

confidence: 99%

Enhanced extended state observer based prescribed time tracking control of wheeled mobile robot with slipping and skidding

Qin,

Yan,

et al. 2024

Intl J Robust & Nonlinear

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This article focuses on the trajectory tracking control for a perturbed wheeled mobile robot (WMR) with slipping and skidding. The external disturbances and uncertainties caused by the slipping and skidding compose the “total” disturbance. By analyzing the stable state of the controlled system, the WMR reference model driven by a favorable disturbance is constructed. This article proposes an enhanced extended state observer (EESO) to reckon the difference between the “total” disturbance and the favorable disturbance. Then, a practical prescribed time tracking method is developed. By introducing a time‐dependent scaling function, the initial value restriction can be relaxed, and the peaking phenomenon caused by the EESO can be tolerated. With the proposed EESO and the prescribed time tracking controller, the estimation error is input‐to‐state stable, and the tracking control of WMR with global prescribed performance is achieved. Simulation results show the advantages.

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Practical fixed-time multi-group time-varying formation for second-order multi-agent systems with actuator attacks and collision avoidance

Zhan,

Lu,

et al. 2024

Information Sciences

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Formation Control of Wheeled Mobile Robots With Multiple Virtual Leaders Under Communication Failures

Cited by 11 publications

References 38 publications

Adaptive Learning Gain based Resilient Control of Multiagent Systems with Partial Uncertain Control Coefficients Under FDI Attacks

Adaptive Learning Gain based Resilient Control of Multiagent Systems with Partial Uncertain Control Coefficients Under FDI Attacks

Enhanced extended state observer based prescribed time tracking control of wheeled mobile robot with slipping and skidding

Practical fixed-time multi-group time-varying formation for second-order multi-agent systems with actuator attacks and collision avoidance

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