PI Piecewise Continuous Observer Design for Sampled and Delayed Linear Systems with Variable Sampling Time Period

Yu Li, Haoping Wang, Yang Tian

2019

Abstract

In recent years, network control systems and visual servo systems have received a lot of attention, but due to network delay and the low sampling rate of visual sensors, it has caused problems for control. In order to reduce the effects of the sampling and delay, this paper deals with proportional integration piecewise continuous observer (PI-PCO), which is based on the theory of a particular class of hybrid systems, called linear piecewise continuous hybrid system (LPCHS). This proposed PI-PCO can estimate the continuous and non-delay state by using the sampled and delayed measurements with variable sampling time period. To show the proposed PI-PCO performance, some numerical simulations with compared results are demonstrated.

Paper Citation

in Harvard Style

Li Y., Wang H. and Tian Y. (2019). PI Piecewise Continuous Observer Design for Sampled and Delayed Linear Systems with Variable Sampling Time Period.In Proceedings of 5th International Conference on Vehicle, Mechanical and Electrical Engineering - Volume 1: ICVMEE, ISBN 978-989-758-412-1, pages 402-407. DOI: 10.5220/0008865304020407

in Bibtex Style

@conference{icvmee19,
author={Yu Li and Haoping Wang and Yang Tian},
title={PI Piecewise Continuous Observer Design for Sampled and Delayed Linear Systems with Variable Sampling Time Period},
booktitle={Proceedings of 5th International Conference on Vehicle, Mechanical and Electrical Engineering - Volume 1: ICVMEE,},
year={2019},
pages={402-407},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008865304020407},
isbn={978-989-758-412-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of 5th International Conference on Vehicle, Mechanical and Electrical Engineering - Volume 1: ICVMEE,
TI - PI Piecewise Continuous Observer Design for Sampled and Delayed Linear Systems with Variable Sampling Time Period
SN - 978-989-758-412-1
AU - Li Y.
AU - Wang H.
AU - Tian Y.
PY - 2019
SP - 402
EP - 407
DO - 10.5220/0008865304020407