Quantum mechanics

Detector

Algorithm

Control (management)

Engineering

Statistics

Event (particle physics)

Systems engineering

Telecommunications

Component (thermodynamics)

Computer science

Mathematical optimization

Bounded function

Filter (signal processing)

Estimation

Thermodynamics

Physics

Mathematics

Estimator

Sampling (signal processing)

Discrete time and continuous time

Mathematical analysis

Artificial intelligence

Geometry

Horizon

Transmission (telecommunications)

Control theory (sociology)

Computer vision

Automatica

This paper is concerned with the moving horizon (MH) estimation problem for linear systems with non-uniform sampling under component-based dynamic event-triggered transmission (DETT) scheme. The sampling interval is allowed to be time-varying with known upper and lower bounds. A so-called component-based DETT scheme is adopted to determine the transmission instant at which an individual sensor sends the measurement to the estimator through certain communication network. Then, a time-varying MH estimator is designed with the corresponding estimation error dynamics characterized by a linear discrete time-varying system whose time-varying parts induced by the non-uniform sampling are modeled by certain norm bounded uncertainties. Sufficient conditions are derived to guarantee the ultimate boundedness of the estimation error. Moreover, within the established theoretical framework, the desired estimator parameter is calculated by solving a set of linear matrix inequalities. Finally, a simulation example is given to illustrate the effectiveness of our proposed MH estimation method.

Moving horizon estimation with non-uniform sampling under component-based dynamic event-triggered transmission