Optimal Self-triggered Control in Networked Control Systems

Abstract

Networked control systems (NCSs) have attracted attentions and have a great advantage that NCSs can reduce costs of installation and have extensive industrial application. On the other hand, the disadvantage that the control performance can be degraded and the plant can be destabilized is happening. Furthermore, data transmission means waste of communication resource and transmission energy when it is not necessary to transmit the packet data. In order to solve the problem, an event-triggered control and self-triggered control are studied. Although these method is attractive, most of recent studies have only focused on an analysis of stability. Therefore, we proposed self-triggered control based on model predictive control to improve the performance furthermore. In addition, Kalman filter is extended and event-driven estimator is derived and employed to the systems. This strategy can reduce transmission rate drastically while guaranteeing the control performance. Eventually, the results are shown and displayed by demonstrating simulations.