LAUSR

Aiming at sustainable development to meet the requirements of Industry 5.0/6.0 revolutions, integrating a resilient, decentralized cyber‐tolerant control framework for large‐scale affine systems is indispensable. This work introduces an intelligent finite‐time cyber‐resilient control framework for an affine system under sensor/actuator deception and denial‐of‐service attacks. First, an adaptive disturbance observer employing a radial basis function neural network (RBF‐NN) has been formulated for smooth and fast estimations of unknown aggregated mismatched uncertainties, which include exogenous disturbance, sensor deception attack, and parametric perturbation. Later, an adaptive finite‐time control law integrated with RBF‐NN is formulated under event‐triggered action for the investigated cyber‐physical affine system. A suitable triggering condition for data communication through the sensor‐to‐controller channel has been derived using the Lyapunov approach, and input‐to‐state stability has been guaranteed under the designed control framework. Numerical simulations with in‐depth qualitative analysis have been showcased to validate the effectiveness and feasibility of the applied control methodology. The suggested control methodology ensures optimal communication medium utilization and is superior in mitigating cyber intrusions.