Robust model predictive control for polytopic uncertain systems via a high-rate network with the FlexRay protocol.

In this article, the robust model predictive control (RMPC) problem is investigated for a class of polytopic uncertain systems over high-rate networks whose signal exchanges are scheduled by the FlexRay protocol (FRP). During signal measurement, a high-rate network is applied to broadcast the data from the sensors to the controller efficiently. The FRP including the characteristics of event-triggered mechanism and the time-triggered mechanism is embedded into the high-rate network to regulate the data transmission in a circular period which can improve the flexibility of data transmission. With the aid of the Round-Robin and Try-Once-Discard protocols, a new expression of the measurement model is formulated by the use of certain data holding strategies. Subsequently, taking both high-rate networks and FRP into account, sufficient conditions are obtained by solving a time-varying terminal constraint set of an auxiliary optimization problem. In addition, an algorithm including both off-line and on-line parts is provided to find a sub-optimal solution. Lastly, two numerical simulations are carried out to substantiate the validity of the proposed RMPC strategy which is based on FRP and a high-rate network.