Input-to-state stabilizability of quantized linear control systems under feedback dropouts

This paper studies the input-to-state stabilizability of quantized linear control systems with external noise under feedback dropouts. A vector of feedback measurements is quantized prior to being transmitted over a communication channel. The transmitted data may be dropped by the channel. The channel dropouts are governed by a stationary model, which is quite general to include many realistic dropout models. This paper derives a lower bound on the constant bit rates which can almost surely stabilize the system in the input-to-state sense under the given dropout condition. A dynamic quantization policy is shown to be able to stabilize the system at that lower rate bound. So the minimum constant stabilizing bit rate has be obtained. The achieved theoretical results are also verified through an example.