[1]LIU Jingwei,ZHAO Hui,ZHOU Rui,et al.Improvement and comparison research between intelligent control systems based on rule based reasoning and neural computation AI methods[J].CAAI Transactions on Intelligent Systems,2017,12(6):823-832.[doi:10.11992/tis.201602015]
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Improvement and comparison research between intelligent control systems based on rule based reasoning and neural computation AI methods

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 12 Number of periods: 2017 6 Page number: 823-832 Column: 学术论文—智能系统 Public date: 2017-12-25
Title:
Improvement and comparison research between intelligent control systems based on rule based reasoning and neural computation AI methods
Author(s):
LIU Jingwei1; 2; 3;  ZHAO Hui4;  ZHOU Rui1;  ZHU Minling3;  WANG Pu5
1. School of Chinese Materia, Beijing University of Chinese Medicine, Beijing 100029, China;
2. Information College, Capital University of Economics and Business, Beijing 100070, China;
3. Computational Transportation Science Center, Capital Univers
Keywords:
intelligent system; intelligent control; advanced control; fuzzy PID; wavelet neural network PID
CLC:
U621；TP273
DOI:
10.11992/tis.201602015
Abstract:
To solve problems, enable real-time online tuning, and to optimize intelligent system parameters during production and daily life usage, different artificial intelligent-classical (AI-CC) control methods and systems are proposed using a combination of different types of artificial intelligent methods and classical control methods . Algorithm improvements are made, and a theoretical analysis comparing the stability and simulation of the AI-CC methods is also implemented. This research achieves the following. Implementation of a fuzzy classical-based intelligent control, and proposal of an incremental improvement algorithm and further adaptive wavelet neural network classical-based intelligent control (AI-CC). A theoretical analysis and stability ensuring method is also proposed and a comparative study undertaken. This research provides results of different types of improved AI-CC methods and a comparative study for use in further academic research, and is expected to enable low cost upgrades and a reliable solution (theoretical guarantee method) for engineering practitioners.
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