Model-based scheduling for networked control systems

Abstract

In this paper, we introduce a model-based scheduling strategy to achieve ultimate boundedness stability in the sensor-actuator networked control systems, where the communication network between the sensor and the network controller is subject to time-varying network induced delays and data-packet dropouts. An estimator and a nominal model of the plant are used explicitly at the controller node to generate control action and schedule control action updates. The data transmissions from the sensor to the network controller are “self-triggered” by imposing the scheduling of the data packet transmissions to meet a soft deadline, while the control action updates generated by the network controller are “event-triggered”, with a new measurement of the nominal model's state obtained to update control action whenever a triggering condition is satisfied or whenever the state of the nominal model is reset by the estimator.