Dual-channel hybrid-triggered adaptive secure tracking control for singularly perturbed fuzzy Markov systems with cyber attacks

This study recapitulates the formulation of a dual-channel hybrid-triggered anti-disturbance adaptive secure tracking controller for singularly perturbed fuzzy Markov jump systems in presence of multi-channel disturbances and false data injection attacks. Typically, a fuzzy augmented hybrid state observer is incorporated for delivering precise assessments of system states and multi-channel disturbances that affect system dynamics and outcomes. Following this, an observer-based adaptive tracking control algorithm is established to ensure robust tracking outcomes. Subsequently, a dual-channel hybrid-triggering scheme is implemented to reduce network overhead, wherein both the measured output and control input are subject to time-triggered protocols and event-triggered mechanisms, independently deciding the transmission of sampled measurement outputs to the observer and control inputs to the actuator. In addition, the control channel is also fortified to resist false data injection attacks for enhancing the system's security. Afterwards, the linear matrix inequalities-based constraints for verifying the stochastic stability of the examined system are derived from Lyapunov Krasovskii functionals. Moreover, the dependability of analysed outcomes is corroborated by graphical depictions generated from numerical simulations.