Inferential networked control with variable accessibility constraints

In this work, an inferential scheme for networked control systems is adressed. An LTI plant with disturbances and measurement noise is assumed to be controlled by a controller that communicates with the sensor and the actuator through a network. This network is assumed to have variable accessibility constraints due to a shared use of it, network-induced delay and packet dropout. In this work a control algorithm is proposed such that the available (and scarce) outputs that arrive delayed on time from its sampling instant are used to make a prediction of the system evolution. That prediction is then used to calculate the control actions that should be applied in the actuator. The algorithm takes into account the possibility of control action drop due to network constraints in order to calculate the control action. This networked control scheme is analyzed in depth and the separation principle between predictor and controller is demonstrated. Both the predictor and controller designs are addressed taking into account the disturbances, the noise measurement, the scarce availability of process output samples and the scarce capability to update the control actions due to the network constraints. Both designs are based on the probability of network availability to transmit the measurements and the input desirable updates on time. The time-varying sampling periods for the input and output of the plant due to the network constraints have been specified and bounded as a function of the probability of success on transmitting the output samples and input updates on a specified time. For both designs H∞ performance has been established and LMI design techniques have been used to achieve a numerical solution.