Descriptor Representation-Based Guaranteed Cost Control Design Methodology for Polynomial Fuzzy Systems

Yu Hsuan Shen, Ying Jen Chen, Fan Nong Yu, Wen June Wang, Kazuo Tanaka

Research output: Contribution to journalArticlepeer-review


This paper presents a descriptor representation-based guaranteed cost design methodology for polynomial fuzzy systems. This methodology applies the descriptor representation for presenting the closed-loop system of the polynomial fuzzy model with a parallel distributed compensation (PDC) based fuzzy controller. By the utility of descriptor representation, the guaranteed cost control (GCC) design analysis can utilize polynomial fuzzy slack matrices for obtaining less conservative results. The proposed GCC design is presented as the sum-of-squares (SOS) conditions. The application of polynomial fuzzy slack matrices leads to the double fuzzy summation issue in the control design. Accordingly, the copositive relaxation works out the problem well and is adopted in the control design analysis. The GCC design minimizes the upper limit of a predesignated cost function. According to the performance function, two simulation examples are provided to demonstrate the validity of the proposed GCC design. In these two examples, the proposed design obtains superior results.

Original languageEnglish
Article number1799
Issue number9
StatePublished - Sep 2022


  • descriptor form approach
  • guaranteed cost control
  • polynomial fuzzy systems


Dive into the research topics of 'Descriptor Representation-Based Guaranteed Cost Control Design Methodology for Polynomial Fuzzy Systems'. Together they form a unique fingerprint.

Cite this