Proceedings of the 2018 International Conference on Computer Science, Electronics and Communication Engineering (CSECE 2018)

Research on Networked Sliding Mode Predictive Controller Based on Particle Swarm Optimization

Authors
Yang Yin, Hongke Li, Zhengying Ren
Corresponding Author
Yang Yin
Available Online February 2018.
DOI
https://doi.org/10.2991/csece-18.2018.50How to use a DOI?
Keywords
Total Ship Computing Environment (TSCE); Networked Control Systems (NCS); Sliding Mode Predictive Control; Particle Swarm Optimization Algorithm (PSO)
Abstract
Aiming at the development of ship information and intellectualization, this paper researched the control law design problems of the network control system under total ship computing environment (TSCE). Firstly, we analyzed and constructed the computing environment network architecture for the development of ship intelligent information technology. Then, the sliding mode predictive control law based on particle swarm optimization was designed for the delay and packet loss problem caused by information network. The control strategy and realization method were analyzed, and the actual control quantity selected at each moment was the optimal sliding mode prediction control signal provided by the actuator. The simulation results showed the effectiveness and robustness of the proposed algorithm.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
Part of series
Advances in Computer Science Research
Publication Date
February 2018
ISBN
978-94-6252-487-3
ISSN
2352-538X
DOI
https://doi.org/10.2991/csece-18.2018.50How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yang Yin
AU  - Hongke Li
AU  - Zhengying Ren
PY  - 2018/02
DA  - 2018/02
TI  - Research on Networked Sliding Mode Predictive Controller Based on Particle Swarm Optimization
PB  - Atlantis Press
SP  - 237
EP  - 241
SN  - 2352-538X
UR  - https://doi.org/10.2991/csece-18.2018.50
DO  - https://doi.org/10.2991/csece-18.2018.50
ID  - Yin2018/02
ER  -