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 a...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transaction on neural networks and learning systems 2021-04, Vol.32 (4), p.1678-1690
Main Authors: Wang, Lijie, Chen, C. L. Philip
Format: Article
Language:English
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
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:2162-237X
2162-2388
DOI:10.1109/TNNLS.2020.2986281