Fuzzy-Model-Based Dynamic Event-Triggered Control in Sensor-to-Controller Channel for Nonlinear Strict-Feedback System via Command Filter

This article considers the situation of sensors transmit plant states to controller in a dynamic event-triggered manner and develops a fuzzy-model-based adaptive command filtered tracking control method for nonlinear strict-feedback systems with uncertain dynamics. First, the dynamic event-trigger rules are designed and implemented in sensor-to-controller channel to reduce the communication frequency in network controlled system. Then, the adaptive fuzzy-model is designed to generate approximated states for controller during the event-trigger intervals to avoid an open-loop like system operation, which can be caused by the traditional zero-order-hold policy. Moreover, command filter technique is incorporated to solve the issue of “jumping of virtual controller” and circumvent “explosion of complexity” problem during the fuzzy-model-based event-triggered controller design process. Meanwhile, the filtering errors are eliminated by compensate signals. Finally, two simulation examples are conducted and the results show the effectiveness and superiority of the proposed method.