Stabilizing uncertain systems with dynamic quantization

We consider state feedback stabilization of uncertain linear systems with quantization. The plant uncertainty is dealt with by the supervisory control framework, which employs switching among a finite family of candidate controllers. For a static quantizer, we quantify a relationship between the quantization range and the quantization error bound to guarantees closed loop stability. Using a dynamic quantizer which can vary the quantization parameters in real time, we show that the closed loop can be asymptotically stabilized, provided that additional conditions on the quantization range and the quantization error bound are satisfied. Our results extend previous results on stabilization of known systems with quantization to the case of uncertain systems.