Minimax control of switching systems under sampling

Considers a general class of systems subject to two types of uncertainty: a continuous deterministic uncertainty that affects the system dynamics, and a discrete stochastic uncertainty that leads to jumps in the system structure at random times, with the latter described by a continuous-time finite state Markov chain. When only sampled values of the system state are available to the controller, along with perfect measurements on the state of the Markov chain, the author obtains a characterization of minimax controllers, which involves the solutions of two finite sets of coupled PDEs, and a finite dimensional compensator. For the linear-quadratic case, a complete characterization is given in terms of coupled generalized Riccati equations, which also provides the solution to a particular H^∞ optimal control problem with randomly switching system structure and sampled state measurements