Event-triggered dynamic output feedback control for networked control systems with probabilistic nonlinearities

This paper investigates the problem of dynamic output feedback control for networked nonlinear systems. A novel event-triggered mechanism (ETM) is proposed, in which a new event-triggering condition is introduced. Compared with some existing ETMs, the proposed ETM has at least three merits: i) The data-releasing rate can be further decreased, leading to a reduction of network loads; ii) During the time when the system is disturbed by external signals, this ETM can release more sampled data to the controller so that some better closed-loop performance can be achieved; and iii) Wrong decision-making on data-releasing can be avoided due to a new definition of the related error. By employing the Lyapunov-Krasovskii functional method, sufficient conditions are derived to design both controller gains and ETM parameters. An example with four cases is given to show the effectiveness and superiority of the proposed method.