Control of Stochastic Systems with Markov Interrupted Observations

Linear discrete-time stochastic systems with abruptly changing parameters in the measurement mechanism are considered. The abrupt changes are modeled by a finite-state Markov chain. The multiple model partitioning approach is used to derive suboptimal control algorithms as the optimal solution is intractable. The proposed approach is illustrated by simulation examples.