Event-Triggered Observation and Control of Positive Complex Networks Using Linear Programming

This paper focuses on the event-triggered observation and control of positive complex networks with randomly occurring nonlinearities obeying a Bernoulli distribution. By utilizing observation errors and sensor measurements, an event-triggered scheme is formulated based on the form of 1-norm. An event-triggered controller is designed by using linear programming. Sufficient conditions are addressed to ensure the positivity of the lower bound of the closed-loop system. By employing a co-positive Lyapunov function, the stability of the upper bound of the closed-loop system is established. Finally, a simulation example is provided to illustrate the efficacy of the proposed design.