Quantized Guaranteed Cost Output Feedback Control for Nonlinear Networked Control Systems and Its Applications

The quantized guaranteed cost static output feedback control problem is investigated for a class of discrete-time nonlinear networked control systems in this article. In this article, the Takagi-Sugeno fuzzy model is put to use for the representation of considered nonlinear networked control systems, where local nonlinear models instead of local linear models are used in the Takagi-Sugeno fuzzy model. Two different dynamic quantizers are applied to quantize the control input and measurement output, respectively. Different from some previous work, a novel guaranteed cost performance function including the quantized control input is used in this article. Through using the S-procedure and introducing some auxiliary scalars, sufficient conditions for the design of guaranteed cost static output feedback controller and dynamic quantizers are obtained in the form of linear matrix inequalities. Finally, the applicability of the proposed method is illustrated through the application in nonlinear mass-spring-damper mechanical system.

Automated summary

This article investigates the quantized guaranteed cost static output feedback control problem for a class of discrete-time nonlinear networked control systems using the Takagi-Sugeno fuzzy model and dynamic quantizers, introducing a novel guaranteed cost performance function and obtaining sufficient conditions through linear matrix inequalities.