Adaptive Control for a Class of Uncertain Nonlinear Systems Subject to Saturated Input Quantization

In this paper, we study the adaptive tracking control problem for a class of uncertain nonlinear systems with input quantization. Different from the existing results, we propose a new quantizer with saturated quantization levels motivated by the saturation property of practical actuators and sensors. With this new quantizer, we know the exact number and values of the quantization levels in advance, regardless of the magnitude of the designed control signal. Thus, we only need to code these quantization levels accordingly such that less network resources are consumed. It is shown that the proposed control scheme guarantees that all the closed-loop signals are globally bounded and the tracking error converges towards a known compact set.