On dynamic real-time scheduling of model predictive controllers

The paper discusses dynamic real-time scheduling in the context of model predictive control (MPC). Dynamic scheduling in this setting is motivated by the highly varying execution times associated with MPC controllers. Premature termination of the optimization algorithm is exploited to trade off prolonged computations versus computational delay. A feedback scheduling strategy for multiple MPC controllers is also proposed, where the scheduler allocates CPU time to the tasks according to the current values of the cost functions. Simulated examples show how the overall control performance may benefit from the application of the proposed schemes.