A Stochastic Model Predictive Controller for Systems with Unreliable Communications

There is a strong trend towards feedback control over communication channels, such as wireless networks. However often communication resources are limited and unreliable, leading to random transmission loss. To deal with this issue, model predictive control seems to be well suited, since it allows to generate future input sequences and the consideration of constraints. A variety of model predictive control formulations that take into account the loss of information have been proposed in the literature. Such methods typically use online optimization of deterministic cost functions and compensate communication effects through buffering at receiving nodes. The present work presents a model predictive control scheme, which adopts a stochastic cost function that explicitly accounts for random packet dropouts. Numerical studies illustrate potential performance benefits of the proposed controller.