Adaptive Event‐Triggered Observer Based Fault‐Tolerant and Anti‐Disturbance Tracking Control for Nonlinear Networked Control Systems

ABSTRACT This study epitomizes the problem of procuring targeted state tracking objectives while ensuring fault tolerance, disturbance suppression and reduced network load for nonlinear networked control systems represented based on interval type‐2 fuzzy framework. In detail, a generalized extended state observer (GESO) is implemented for concurrent assessments of system states alongside providing the controller with estimations of actuator faults and external disturbances to counteract their detrimental effects on the system behaviour. Further, a model reference system incorporating fuzzy membership is included to construct the indented tracking control algorithm. Specifically, the state information extracted from GESO is propagated to the established tracking control protocol by means of adaptive event‐triggered mechanism to reduce network load while ensuring peak performance. Altogether, the intended targets are achieved by devising a GESO‐based adaptive event‐triggered model‐reference tracking controller. Notably, through the employment of fuzzy membership‐linked Lyapunov–Krasovskii functionals, we set forth the necessary prerequisites for obtaining asymptotic stability for the configured system specified by linear matrix inequalities (LMIs). Certainly, to substantiate the utility of assembled controller, numerical findings are conveyed through graphical plots.