Analytical Controller Design for Model-Following Control Systems Considering Input-Output Quantization

Abstract

In control systems using network communication or digital sensors, the quantization of input and output signals can significantly impact control performance. Therefore, it is essential to incorporate signal quantification into the control system design to prevent performance degradation. This study proposes a controller design method for systems in which both inputs and outputs are quantized. The proposed method derives a controller that minimizes the upper bound of the error between a plant output and a reference model output. In contrast to previous studies, our proposed method avoids solving matrix inequalities numerically and provides an analytical design approach.