DOI: 10.1049/cth2.12776 ISSN: 1751-8644

Adaptive inverse control for trajectory tracking with dead‐zone nonlinearity under cyberattacks

Farnaz Sabahi

Abstract

Control systems rely heavily on the accuracy and reliability of sensor data; however, the integrity of these data can be compromised through spoofing attacks, leading to significant modelling errors that can render control impractical. In addition, centralized control poses a significant threat to system security. To address these issues, a distributed framework is suggested for a discrete‐time nonlinear system that encounters unknown dead‐zones at its input. The framework uses the inherent resilience of a decentralized peer‐to‐peer network to secure information exchange, eliminating the need for prior knowledge of system dynamics or potential attacks. The proposed framework performs two complex tasks: identifying the nonlinear system and dealing with the unknown nonlinearity at the input in the form of a dead‐zone. An adaptive dead‐zone inverse is used to handle the unknown nonlinearity at the input in the form of a dead‐zone and integrate blockchain technology to secure communication between components. The blockchain component ensures tamper‐proof data transmission and resistance to cyberattacks, providing both detection and defence mechanisms without prior knowledge of system dynamics or potential attacks. The actuator and plant components are matched and synchronized using a private network with static nodes, ensuring deterministic and well‐coordinated communication. Simulation results demonstrate that the proposed framework both with and without blockchain integration, maintains stability and outperforms traditional methods in terms of robustness and accuracy, even when all parts of the framework are adjusted in response to attacks.

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