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Article

Adaptive Sliding Mode Resilient Control of Multi-Robot Systems with a Leader–Follower Model under Byzantine Attacks in the Context of the Industrial Internet of Things

School of ICT, University of Tasmania, Invermay 7248, Australia
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Author to whom correspondence should be addressed.
Machines 2024, 12(3), 205; https://doi.org/10.3390/machines12030205
Submission received: 29 January 2024 / Revised: 12 March 2024 / Accepted: 14 March 2024 / Published: 20 March 2024
(This article belongs to the Special Issue Optimization and AI of Autonomous Multi-Agents)

Abstract

In this paper, an adaptive and resilient consensus control mechanism for multi-robot systems under Byzantine attack, based on sliding mode control, is proposed. The primary aim of the article is to develop a finite-time consensus control strategy even in the presence of a Byzantine attack. In the start, a finite-time consensus control mechanism is proposed to identify the essential conditions required for ensuring consensus accuracy in multi-robot systems, even when faced with Byzantine attacks using Lyapunov theory. Subsequently, a sliding mode control is combined with an adaptive technique for multi-robot systems that lack prior knowledge of Byzantine attack. Later, an attack observer is proposed to estimate the performance of multi-robot systems in the presence of a Byzantine attack. Additionally, chattering effects are mitigated by employing integral sliding mode control. As a result, resilient consensus performance of multi-robot systems can be achieved in a finite time interval. A simulation example is also presented to validate the effectiveness of the proposed model. Furthermore, we delve into the data structure of the proposed method and explore its integration with Artificial Intelligence for seamless incorporation into the Industrial Internet of Things applications.
Keywords: resilient consensus; multi-robot system; sliding mode control; Byzantine attack; Industrial Internet of Things; recurrent neural network; time series; digital twins resilient consensus; multi-robot system; sliding mode control; Byzantine attack; Industrial Internet of Things; recurrent neural network; time series; digital twins

Share and Cite

MDPI and ACS Style

Nasir, M.; Maiti, A. Adaptive Sliding Mode Resilient Control of Multi-Robot Systems with a Leader–Follower Model under Byzantine Attacks in the Context of the Industrial Internet of Things. Machines 2024, 12, 205. https://doi.org/10.3390/machines12030205

AMA Style

Nasir M, Maiti A. Adaptive Sliding Mode Resilient Control of Multi-Robot Systems with a Leader–Follower Model under Byzantine Attacks in the Context of the Industrial Internet of Things. Machines. 2024; 12(3):205. https://doi.org/10.3390/machines12030205

Chicago/Turabian Style

Nasir, Muhammad, and Ananda Maiti. 2024. "Adaptive Sliding Mode Resilient Control of Multi-Robot Systems with a Leader–Follower Model under Byzantine Attacks in the Context of the Industrial Internet of Things" Machines 12, no. 3: 205. https://doi.org/10.3390/machines12030205

APA Style

Nasir, M., & Maiti, A. (2024). Adaptive Sliding Mode Resilient Control of Multi-Robot Systems with a Leader–Follower Model under Byzantine Attacks in the Context of the Industrial Internet of Things. Machines, 12(3), 205. https://doi.org/10.3390/machines12030205

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