\(H_{\infty }\) Control of Nonlinear Networked Cascade Control System under Multi-channel Quantization and Event-triggered Mechanism

In this paper, the problem of state feedback quantized controller design for nonlinear networked cascade control system under multi-channel adaptive event-triggered strategy is studied. Based on the Takagi-Sugeno fuzzy model, the nonlinear system is modeled. An improved adaptive event-triggered mechanism is proposed, in which the dynamic threshold function is composed of multiple dynamic sub-functions, and the sampling data and trigger data of the sensor-controller are fully considered, which significantly alleviates the network burden of the communication channel. In addition, the dynamic quantization parameters of the dynamic quantizer are improved. The dynamic quantization parameters are coordinated by the quantized signal and the original parameters, which ensures that there is no singularity problem in the dynamic quantization parameters. Finally, the effectiveness and superiority of the proposed design method are verified by simulation examples.