Robust Fuzzy Feedback Control for Nonlinear Systems With Input Quantization

Authors：Pan, Ting-Ting; Chang, Xiao-Heng^*; Liu, Yi

Source：IEEE Transactions on Fuzzy Systems, 2022, 30(11): 4905-4914.

DOI：10.1109/TFUZZ.2022.3163908

• Input quantization
• norm-bounded uncertainties
• robust control
• Takagi-Sugeno (T-S) fuzzy systems

In this article, we study the robust quantized feedback control problem for nonlinear discrete-time systems that are described by Takagi-Sugeno (T-S) fuzzy model with norm-bounded uncertainties. The dynamic quantizer composed of a dynamic parameter and a static quantizer is considered to quantize the control input signal. An improved two-step approach to design controller and dynamic quantizer for T-S fuzzy system is proposed based on the LMI technique. In the first step, a robust controller is designed to guarantee that the quantized fuzzy closed-loop system with norm-hounded uncertainties is asymptotically stable with prescribed H-infinity performance. Then, the parameter-dependent (membership function) scalar variable is obtained to determine the dynamic quantizer's parameter in the second step. Finally, the simulation result of truck-trailer system is presented to validate the effectiveness and feasibility of the proposed two-step design approach.