Dynamic event-triggered model-free adaptive control for networked control systems with random packet loss

A novel dual-channel dynamic event-triggered model-free adaptive control method with compensation is proposed for nonlinear networked control systems (NCSs) subjected to random packet loss. In order to tackle the issue of redundant data transmission, a dual-channel triggering control framework is designed, where data transmission only occurs upon meeting the triggering conditions. Compared with the traditional static event-triggered schemes with fixed triggering thresholds, the proposed method allows for dynamically adjustable triggering thresholds. This means that the number of data transmissions in the forward and feedback channels can be further reduced. In addition, considering the detrimental impact of random packet loss and output event-triggered on the system, compensation is applied to the system's output data using the linear data model of the nonlinear system, which is directly derived from I/O data without incorporating any other mechanistic model information, thereby ensuring optimal control performance. In contrast to existing results, the proposed control strategy can enhance system performance while conserving network communication resources. The effectiveness and superiority of the proposed scheme have been validated through two simulations.