Reduced-Order Observer-Based Dynamic Event-Triggered Adaptive NN Control for Stochastic Nonlinear Systems Subject to Unknown Input Saturation

In this article, a dynamic event-triggered control scheme for a class of stochastic nonlinear systems with unknown input saturation and partially unmeasured states is presented. First, a dynamic event-triggered mechanism (DEM) is designed to reduce some unnecessary transmissions from controller to actuator so as to achieve better resource efficiency. Unlike most existing event-triggered mechanisms, in which the threshold parameters are always fixed, the threshold parameter in the developed event-triggered condition is dynamically adjusted according to a dynamic rule. Second, an improved neural network that considers the reconstructed error is introduced to approximate the unknown nonlinear terms existed in the considered systems. Third, an auxiliary system with the same order as the considered system is constructed to deal with the influence of asymmetric input saturation, which is distinct from most existing methods for nonlinear systems with input saturation. Assuming that the partial state is unavailable in the system, a reduced-order observer is presented to estimate them. Furthermore, it is theoretically proven that the obtained control scheme can achieve the desired objects. Finally, a one-link manipulator system and a three-degree-of-freedom ship maneuvering system are presented to illustrate the effectiveness of the proposed control method.

Automated summary

This article presents a dynamic event-triggered control scheme for stochastic nonlinear systems with unknown input saturation and partially unmeasured states. A dynamic event-triggered mechanism and an improved neural network are designed to achieve resource efficiency and to approximate unknown nonlinear terms. An auxiliary system is constructed to handle asymmetric input saturation, and a reduced-order observer is presented for estimating partially unmeasured states, with theoretical evidence of achieving desired control objectives. The effectiveness of the proposed control method is illustrated through examples of a one-link manipulator system and a three-degree-of-freedom ship maneuvering system.