Resource constrained LQR control under fast sampling

We investigate a state feedback Linear Quadratic Regulation problem with a constraint on the number of actuation signals that can be updated simultaneously. Such a constraint arises for example in networked and embedded control systems, due to limited communication and computation capabilities. Following recent results on the dual problem of scheduling Kalman filters, we first develop a bound on the achievable performance that can be computed efficiently by semidefinite programming. This bound can be approached arbitrarily closely by an analog periodic controller that can switch between control inputs arbitrarily fast. We then discuss implementation issues on digital platforms, i.e., the discretization of the analog controller in the presence of a relatively fast but finite sampling rate.