  When multiple model predictive controllers are implemented on a shared
control area network (CAN), their performance may degrade due to the
inhomogeneous timing and delays among messages. The priority based real-time
scheduling of messages on the CAN introduces complex timing of events,
especially when the types and number of messages change at runtime. This paper
introduces a novel hybrid timing model to make runtime predictions on the
timing of the messages for a finite time window. Controllers can be designed
using the optimization algorithms for model predictive control by considering
the timing as optimization constraints. This timing model allows multiple
controllers to share a CAN without significant degradation in the controller
performance. The timing model also provides a convenient way to check the
schedulability of messages on the CAN at runtime. Simulation results
demonstrate that the timing model is accurate and computationally efficient to
meet the needs of real-time implementation. Simulation results also demonstrate
that model predictive controllers designed when considering the timing
constraints have superior performance than the controllers designed without
considering the timing constraints.
