Adaptive event-triggered control over a shared network

Under many circumstances event-triggered control outperforms time-triggered control schemes when resources such as communication, computation, or energy are sparse. This paper investigates another benefit of event-triggered control concerning the ability of adaptation. The system under consideration comprises multiple heterogeneous control loops that are closed over a shared communication network. Each subsystem is modelled as a discrete-time stochastic linear system. The design problem is formulated as an average cost Markov decision process (MDP) with unknown global system parameters that are to be estimated during execution. Techniques from distributed optimization and adaptive MDPs are used to develop distributed self-regulating event-triggers that adjust their transmission rate to meet a global resource constraint. Numerical simulations show the effectiveness of the approach and illustrate the convergence properties.