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    Abstract
2017 (Vol. 13, Issue: 3)
Research Article

The Model Relief Food Free Control Technology Based on the Cascade Observer

1, 2Hongcheng Zhou and 2Daobo Wang
1Institute of Information, JinLing Institute of Technology, Nanjing 211169
2College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
 

DOI: 10.19026/ajfst.13.4145
Submitted Accepted Published
July ‎26, ‎2015 August ‎20, ‎2015 March 25, 2017

  How to Cite this Article:

1, 2Hongcheng Zhou and 2Daobo Wang, 2017. The Model Relief Food Free Control Technology Based on the Cascade Observer.  Advance Journal of Food Science and Technology, 13(3): 104-109.

DOI: 10.19026/ajfst.13.4145

URL: http://www.maxwellsci.com/jp/mspabstract.php?jid=AJFST&doi=ajfst.13.4145

Abstract:


In this study, the methods are applied to the control of the relief food helicopter and achieve good control performance and effect. The design of the fuzzy controller does not depend on the model of the controlled object. But it depends very closely on the experiences and knowledge of control experts or operators. But it is difficult to design a high-level fuzzy controller. Moreover the fuzzy controller is not easy to control learning and adjustment of the parameters, which makes the structure of the self-adaptive fuzzy controller difficult. Self-adaptive learning technology can effectively compensate for the decline of control performance caused by the imperfection of the rule base. The self-adaptive fuzzy control has two kinds of forms.

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    Competing interests

The authors have no competing interests.
    Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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© The Author(s) 2017

ISSN (Online):  2042-4876
ISSN (Print):   2042-4868
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