Sampled-data Control for T-S Fuzzy Systems with Quantized Signals

Quantized guaranteed cost dynamic output feedback control for uncertain nonlinear networked systems with external disturbance

“…The stabilization problem for nonlinear NCSs which considered quantization and delay simultaneously was studied by using the Lyapunov functional method by Zhang et al (2010). The sampled-data control problem for nonlinear T-S fuzzy model with quantization was addressed by Han et al (2018), who designed the sampled-data controller by applying dynamic quantizer as well as the input delay method. To meet the requirement of stability for the fault T-S fuzzy systems, Li et al (2020a) explored a novel sliding mode control (SMC) strategy on the basis of event-triggered adaptive control, wherein the dynamic uniform quantizers were utilized for the data quantization, and the quantized state signals were regarded as the condition of event-triggered.…”

“…The nonfragile H ∞ filtering issue for nonlinear switched systems was presented by Zheng et al (2020), who simultaneously considered the filter parameter disturbance and the static data quantization in the T-S fuzzy model. It is worth noting that all of Zhang et al (2010), Han et al (2018), Li et al (2020a). and Zhang et al (2011) adopted dynamic quantization strategy to quantize the signals, but none of them took the external disturbances which are unavoidable in practical situations into consideration.…”