Event-triggered Sampling Strategy Design to Optimize the Performance of a Scalar System Under Feedback Communication Constraints

Abstract

This paper aims to optimize the performance of a scalar continuous-time linear time-invariant system, whose feedback information is transmitted through a rate-constrained communication network with random network delay. Due to the limitation of feedback network resources, the feedback information can not be available to the controller precisely and continuously. Moreover, the random transmission delay will reduce the amount of feedback information and degrade the performance of the concerned system. To resolve the above issues, we propose an event-triggered sampling strategy that can utilize the transmission resources more efficiently. Compared with the optimal time-driven sampling strategies and the optimal Lebesgue sampling strategies, our event-triggered sampling strategy can guarantee better performance under the same transmission constraints. The effectiveness of the proposed event-triggered sampling strategies is further illustrated via simulations.