A High-Gain Approach to Event-Triggered Control with Applications to Motor Systems

In this paper, an event-triggered high-gain-observer-based output feedback control scheme is introduced by designing separate event-triggering conditions, which only rely on the measurable signals of the controlled system for the system outputs and the control signal, and the performance of the proposed control scheme is investigated. Quantitative relationships between the asymptotic upper bounds of the observation error and the parameters of the event-based sampler are developed to quantify the effect of event-based sampling. The theoretic analysis shows that the observation error can be guaranteed to be asymptotically bounded, and the closed-loop system can be guaranteed to be asymptotically stabilized. Comparative experiments are carried out on a dc torque motor system to validate the theoretic results, and the experimental results indicate that the proposed control strategy can achieve satisfactory control performance.