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

• Published in: IEEE transaction on neural networks and learning systems Vol. 32; no. 4; pp. 1678 - 1690
• Main Authors: Wang, Lijie, Chen, C. L. Philip
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.04.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Actuators; Adaptive control; Artificial neural networks; Control methods; Dynamic event-triggered mechanism (DEM); improved neural network (NN); input saturation; Multi-agent systems; Neural networks; Nonlinear control; Nonlinear dynamical systems; Nonlinear systems; Observers; Parameters; reduced-order observer; Saturation; Ships; stochastic nonlinear systems; Stochastic systems; Stochasticity

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 a...